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Customer journey report steps and filters

Last updated: March 13, 2024

Available with any of the following subscriptions , except where noted:

When creating a customer journey report , use steps and filters to define the journey a contact or deal must take. The sections below highlight some of the most common steps and filters to use in your customer journey analytics report.

Steps are the individual events that a contact or deal must complete to move on to the next stage in the journey. Multiple steps can be included in a stage.

Ad interactions: the time when a visitor engaged with an ad connected to the HubSpot account. HubSpot can capture ad interactions that occurred from users who haven’t yet converted into a contact in your HubSpot account, this means that this event supports anonymous visitors.

Learn more about using ads in HubSpot .

Calls started: the time when the start of a call with a contact began. Use Calls started to measure whether a rep placed a call with a contact. This event captures a call whether or not it is outbound (i.e., began on the contact record or in the conversations inbox) or inbound (i.e., the user called in and the call was logged to their CRM record).

Calls ended: the time of the end of a call with a contact. This event captures a call whether or not it is outbound (i.e., began on the contact record or in the conversations inbox) or inbound (i.e., the user called in and the call was logged to their CRM record).

Learn more about using calling in HubSpot .

Campaign ID: populates the campaign that the interaction is associated with.

CTA views: the time when a visitor or contact viewed a CTA. HubSpot can track CTA views regardless of whether or not the person is a contact in your HubSpot account, this means that this event supports anonymous visitors.

CTA clicks: the time when a visitor or contact clicked a CTA. HubSpot can track CTA clicks regardless of whether or not the person is a contact in your HubSpot account, this means that this event supports anonymous visitors.

Deal stage: populates deal stage data from any of your pipelines.

Contacts finished viewing documents: the time when a contact in your account finished viewing a document.

Contacts viewed documents: the time when a contact in your account began viewing a document.

Documents shared with contacts: the time when a HubSpot user shared a document with a contact. This event is tracked when a document is sent to a contact through an email or sequence where the user's inbox is connected to HubSpot.

Learn more about using documents in HubSpot .

Form view: the time when someone’s browser loaded a form on their screen, meaning the user had scrolled to the point that they could view the form. HubSpot can capture form views that happened from users who haven’t yet converted into a contact in your HubSpot account.

Form interaction: the time when someone began filling out a form. This event is captured when someone has clicked into the form and/or has begun to fill out the form. HubSpot is able to capture form interactions that happened from users who haven’t yet converted into a contact in your HubSpot account.

Form pop up view: the time when someone’s browser loaded a pop up form on their screen. This is specific to pop up forms and happens when the HubSpot tracking code registers that the user’s browser loaded the form. HubSpot can capture pop up form views that happened from users who haven’t yet converted into a contact in your HubSpot account.

Form submission: the time when someone successfully submitted a form. Form submissions require a user to provide their email address. Therefore, this event does not need to have the ‘include anonymous visitors’ option checked to see all form submissions in a journey report.

Learn more about using forms in HubSpot .

Marketing emails

Clicked links in email: the time when a contact clicked a link in a marketing email.

Emails bounced: the time when an email sent to a contact bounced.

Emails delivered: the time when an email sent to a contact was delivered successfully.

Opened emails: the time when a contact opened a marketing email.

Reported spam: the time when a contact marked an email as spam.

Updated email subscription status: the time when a contact updated their email subscription status.

Marketing events

Attended marketing event: the date and time when a contact attended a marketing event.

Canceled marketing event: the time when a contact canceled their registration for a marketing event invitation.

Registered for marketing event: the time when a contact registered to attend an upcoming marketing event.

Learn more about marketing events in HubSpot .

Media played: the time when a contact played a media file stored in your HubSpot account.

Meetings booked: the time when a contact scheduled to attend a meeting. This can either happen when a contact books through a HubSpot meeting link or a HubSpot user schedules a meeting with a contact directly from the record. 

Meeting outcome changes: tracks when a contact’s meeting outcome was changed or set. On the contact record, HubSpot users can set the meeting outcome. For example, the meeting outcome could be Scheduled , Completed , No show , etc. This event tracks when this value has been set.

Outbound message deliveries: the time when a WhatsApp message was delivered to a contact. Outbound message failures: the time when a WhatsApp message failed to deliver to a contact. Outbound message opens: the time when a contact opened a WhatsApp message. Outbound message sends: the time when a WhatsApp message was sent to a contact.

Learn more about using WhatsApp in HubSpot .

Payment failed: the t ime when a contact’s recurring card or bank transfer payment failed to process.

Payment initiated: the t ime when a contact’s bank transfer payment was initiated.

Payment refund failed: the t ime when a contact’s payment refund failed to complete.

Payment refund initiated: the t ime when a contact’s payment refund began.

Payment refund succeeded: the t ime when a contact’s payment refund was completed.

Payment succeeded: the t ime when a contact’s payment was successfully processed.

Learn more about using payments in HubSpot .

Sales email

Sales email clicks: the time when a contact clicked a link in a one-to-one email.

Sales email opens: the time when a contact opened a one-to-one email.

Sales email replies: the time when a contact replied to a one-to-one email.

Sales email sends: the time when an one-to-one email was sent to a contact.

Learn more about sending one-to-one email in HubSpot .

Contacts booked meetings through a sequence: the time when a contact booked a meeting through a sequence.

Contacts enrolled in a sequence: the time when a HubSpot user enrolled a CRM into a sequence.

Contacts unenrolled in a sequence: the time when a contact is no longer enrolled in a sequence. This could happen because the contact booked a meeting through the sequence, replied to an email in the sequence, unsubscribed from the sequence, or the sequence came to an end.

Contacts unenrolled manually from sequence: the time when a HubSpot user manually unenrolled a contact from a sequence.

Contacts unsubscribed from sequence email: the time when a contact unsubscribed from a one-to-one email while enrolled in a sequence.

Sequence emails bounced: the time when an email sent to a contact bounced.

Sequence steps executed: the time when a step was executed in a sequence.

Sequences errored: the time when an error occurred in a sequence.

Sequences finished: the time when a contact reached the final step of a sequence.

Learn more about using sequences in HubSpot .

Link in short messages clicked: tracks when a contact clicked a message in an SMS message. Short messages delivered: tracks when an SMS message was delivered to a contact. Short messages dropped: tracks when an SMS message was delivered to a contact but was dropped. Short messages failed: tracks when an SMS message failed to deliver to a contact. Short message sent: tracks when an SMS message was sent to a contact.

Learn more about using SMS messaging in HubSpot .

Pages visited: the time when a visitor viewed a page that was tracked by the HubSpot tracking code . HubSpot is able to capture page visits and interactions that happened from users who haven’t yet converted into a contact in your HubSpot.

After adding your steps you can use the below filters to further refine your report:

Ad campaign ID: populates the ad campaign that the ad interaction is associated with.

Ad network: populates the name of the network where the interaction occurred. (i.e. Facebook, Google, and LinkedIn.) Learn more about ad tracking in HubSpot .

Interaction type: populates which type of interaction occurred. An interaction can include either a site visit or a form submission..

Network placement: populates the different methods of publishing ads. For example, Facebook Messenger or Google Display Network.

Call owner: the user who initiated the call.

Call country: the country where the call recipient received the call.

Content ID: populates the content pages where the CTA is. For example, the name of a specific blog post or a specific landing page where a CTA is embedded will display in the dropdown menu.

CTA guid: populates the specific name of a CTA. 

Content ID: populates the content pages where the form is placed. For example, the name of a specific blog post or a specific landing page where a form is embedded will display in the dropdown menu.

Form ID: populates the specific name of a form.

Business units: filter by any of the business units you’ve set up in your account. Learn more about business units .

Email content ID: filter by the unique name of the marketing email.

Original URL:  the specific URL a contact clicked in your email. 

Event name: filter by the specific name of a webinar. This allows you to view which specific marketing events are generating the most interest, indicating which types of content you should be creating more of.

Origin: filter by two options; Online or in-person.

Learn more about using marketing events .

Content page: populates the specific content pages where media has been embedded. For example, you could analyze a specific landing page where a video is embedded.

Meetings booked: measures when a contact books a meeting that is logged in your HubSpot account. This can occur through a meeting link or when a meeting is logged on a contact record.

Meeting outcome (only available when using meeting outcome changes step): allows you to take the journey a step further and specify the result of the meeting in the journey. You can see multiple meeting outcomes in a single stage by using branching.

Form ID: if a meeting link is connected to a form, you can filter to only include meetings that are tied to a specific number of forms.

Meeting owner: filter by a specific meeting owner. This is useful if you want to view how prospects and customers are flowing through specific reps, which can provide opportunities to see if a particular group of reps are yielding better results.

Meeting type: filter by Round Robin , Personal , or Group to view if one meeting type creates a higher conversion rate.

User ID: populates the name of the different users in your HubSpot account who are emailing prospects. Unlike sequence enrollment, a HubSpot user does not need to enroll a prospect into a sequence for this to count in the journey report, they only need the HubSpot sales extension to be installed in their email. This property allows you to see if a specific sales rep is driving higher engagement than others, allowing you to analyze what the rep may be doing differently.

Enrolled by user: populates the different users in your HubSpot account who are using the sequences tool to engage prospects.

Sequence ID: populates the unique sequences in your HubSpot account that reps can use to nurture prospects. A unique Sequence ID is generated each time a user enrolls a prospect into a new sequence.

Template ID: populates the name of templates that you have set up in your HubSpot account for users to nurture prospects.

Content ID: allows for a like-for-like comparison between any blog posts, landing pages, and more. You can analyze if a certain piece of content is resonating more with web visitors.

Advanced tracking code properties

Many properties are unique to your HubSpot account and require you to manually input the values. This is especially true for interactions that rely on the HubSpot tracking code.

Some of the most popular properties that require you to manually input values are listed below. 

• Browser: allows you to filter based on a specific browser, like Chrome, Safari, Firefox, etc. You can view this data in the Traffic Analytics tool .
• Content type: allows you to choose a specific type of your website. For example, you can choose between blog posts, landing pages, website pages, and knowledge base articles. Learn more here .
• Country: allows you to filter on a specific country as defined by the International Organization for Standardization. For example, ‘US’ would filter to web traffic from the United States, while ‘DE’ would filter to web traffic from Germany. For a full list of country codes, reference the Alpha 2 column .
• Device type: allows you to filter on what type of device was being used when a visitor engaged with your brand. For example, you can use ‘desktop’ or ‘mobile’. Learn more about device types .
• Region: allows you to filter on a specific subdivision (e.g. a province or state) of a country as defined by the International Organization for Standardization. For example, ‘TN’ would filter to web traffic from the American state of Tennessee while ‘75C’ would filter to web traffic from the French metropolitan of Paris. View the full list of region codes from the United Nations Economic Commision for Europe .

Related content

• Create tracking URLs
• Create custom events codelessly with the event visualizer
• Create reports with the custom report builder

How to Leverage HubSpot Customer Journey Analytics

Hubspot customer journey analytics can help product managers tap into the pulse of their target customers.

You can understand their journey, gain insights to improve their experience and connect your customer experience efforts to desired financial outcomes.

This article discusses how the HubSpot customer journey analytics reporting tool can help you attract customers and accurately walk them through every step of the customer journey.

• HubSpot customer journey analytics is a powerful data-led tool that drives improved decision-making and conversions .
• Benefits of the customer journey analytics tool include unifying your data, creating a path for revenue generation , and optimizing your marketing investments.
• HubSpot has a robust pricing model with five major plans for analytics: Marketing Hub, Sales Hub, Service Hub, Operations Hub, and CMS Hub.
• Userpilot integrates with HubSpot to help you better analyze customer data and make data-driven decisions.

Overview of HubSpot customer journey analytics

Customer journey analytics from HubSpot is a powerful reporting tool that aggregates all the interactions a contact has with your business. It makes sense for marketers who want to unlock valuable insights , ensure better decision-making, and drive conversions.

The benefits of using Hubspot Marketing Hub for customer journey analytics

• Connect every customer interaction to revenue : You can visualize the impact of your email marketing campaigns, social media campaigns, and other marketing efforts with the customer journey analytics reporting tool. By connecting your marketing and sales efforts, you can focus your budget on activities that yield the biggest impact.
• Analyze conversion rates and time between steps : Analyzing conversion rates and time between touchpoints will help you understand what works and what doesn’t. This way, you can improve your strategies and build a more robust customer journey pipeline.
• Create an ideal customer journey that drives revenue : You can create optional touchpoints since all customers do not follow the same journey to conversion. Acknowledging the multiple paths customers can take can help you create a customer journey that drives revenue.
• Optimize your marketing investments : With the customer journey analytics feature on HubSpot, you can optimize your campaigns and make smarter budgeting decisions.
• Unify your data to deliver better customer experiences : You can combine data using the flexible and customizable HubSpot marketing dashboards to see the initiatives that yield the best results for your business.

How to create a customer journey analytics report in HubSpot

Note : The following limits apply when creating customer journey analytics reports on HubSpot:

• HubSpot lets you add up to 15 stages and up to 15 unique steps. For instance, you can add 15 stages and set one step per stage or five steps in the first stage, second stage, and third stage to achieve a total of 15 stages.
• You can analyze spanning a period of three years or up to twenty million events. If your report is configured when there are over twenty million events, the date range window will be reduced to a single month.

Here are six steps to creating a journey report that can help you understand the impact of every interaction with your business:

Step 1: Create a journey report

• Navigate to Reporting > Reports in your HubSpot account.
• In the upper right corner, click Create Report.
• From the Create Report section, go to the Build from Scratch tab and click Customer Journey Reports.

Step 2: Select a data source:

When creating a journey report, you can choose from two data sources:

• Contacts (available on Marketing Hub Enterprise only): select Contacts to get insights on how your content is creating new contacts.
• Deals (available on Sales Hub Enterprise only): select Deals to get insights on how your content is creating new deal opportunities.

Step 3: Add the steps in the customer’s journey report

• In the left corner, you will find different steps, such as Emails bounced, Emails delivered, Opened emails, etc.
• Click and drag the steps to the Stage section. You can add up to 15 steps leading to a goal or conversion.

Step 4: Filter the selected properties

• Click the filter icon > Select property > Apply to configure your step.

Step 5: Configure your journey reports with branches or optional steps

• To further customize your journey report, you can add branches or make steps optional.
• Add branches by clicking and dragging a Step to the Create a branch section. This will create two paths within a stage to allow a contact to complete either path in the stage.
• To mark a step as optional, select Mark as optional. This will mean that a contact must not go through that step to complete the journey. Any contact that makes it to the last step of the journey will be part of the total conversion rate.

Step 6: Run the report to display your data

• Click Run Report once you are done configuring your journey. This will have your data displayed on the right panel, then filter your data with the filter icon at the top of the panel.
• You can view your data by Contacts, Deals, and Date Range.

Save your customer journey reports

Click Save Report in the top right corner.

Set the access permissions for the report, then click Save.

What common properties can you use in your contact customer journey analytics reports?

Let us discuss some of the most common properties you can use in your contact customer journey analytics reports.

Ads and Campaigns

• Ad campaign ID : populates the advertising campaign linked to the ad interaction.
• Ad network : populates the network where the interaction took place, such as Linkedin, Facebook, and Google.
• Interaction type : populates the type of interaction that occurred. This may include a form submission or a website visit.
• Network placement : populates the different advertising deployment methods, such as Google Display Network and Facebook Messenger.
• Campaign ID : populates the campaign linked to the interaction.

CTAs and Deals

• Content ID : populates the content pages containing the call-to-action (CTA). For instance, the dropdown menu will show the names of specific blogs or landing pages where the CTA is.
• CTA guide : populates the name of the call-to-action (CTA).
• Deal stages : populates deal stage information from any of your pipelines.
• Content ID : populates content pages containing the form placement. For instance, the dropdown menu will show the names of specific blog posts or landing pages where a form is embedded.
• Form ID : populates the name of a form.

Marketing emails and marketing events

• Event name : filter based on the specific name of the webinar. This enables you to identify which events are attracting the most interest, providing insights into the types of content you should prioritize for future creation.
• Origin : allows you to filter by either Online or in-person.
• Business units : allows you to filter business units in your account.
• Email content ID : allows you to filter by the unique marketing email name.
• Original URL : the URL clicked by a contact in your email.

Sequences and web pages

• Enrolled by user : populates the different users within your HubSpot account who are using it to engage with prospects.
• Sequence ID : populates unique sequences in your HubSpot account that representatives can use for nurturing prospects. Every time a user enrolls a prospect into a new sequence, a unique sequence ID is generated.
• Template ID : populates the template names in your HubSpot account for users to nurture prospects.
• Content ID : allows for direct comparison between blog posts, landing pages, etc. As a result, you can determine if a particular content appeals to your website visitors.

Advanced tracking code properties

• Browser : allows filtering based on a particular browser, such as Google Chrome, Firefox, etc. You can use the Traffic Analytics tool to access and analyze this data.
• Content type : you can choose a specific website type. For example, you can select between blog posts, website pages, landing pages, etc.
• Country : allows you to filter based on specific countries using country codes as defined by the International Organization for Standardization. For instance, ‘CA’ would filter web traffic from Canada while ‘GB’ would filter web traffic from the United Kingdom.
• Device type : allows filtering based on the device a visitor uses when they engage with your brand. For example, you can filter using ‘mobile’ or ‘desktop’.
• Region : allows filtering based on a country’s subdivision. For example, ‘ID-RI’ would filter web traffic from the Riau province of Indonesia while ‘TN’ would filter web traffic from Tennessee in America.

How much does HubSpot’s customer journey analytics reporting tool cost?

HubSpot offers five pricing plans to help you understand customer behavior and attract the right customers: Marketing Hub, Sales Hub, Service Hub, Operations Hub, and CMS Hub.

Marketing Hub Starter, Professional

The Marketing Hub Starter plan is priced at $20 per month ($18 monthly for annual subscriptions) for 1,000 leads. HubSpot customers on the Starter plan have access to A/B testing, ad conversion events, campaign management, and more.

Marketing Hub Professional is priced at $800 monthly for the first 2,000 leads. It offers everything in the Starter, plus lead scoring, Salesforce integration, and custom lead scoring criteria.

Sales Hub Starter, Professional

The Sales Hub Starter plan starts at $20 monthly ($18 monthly for annual subscriptions) for two users. Some of its features include sale automation, product library, meeting scheduling, and standard CRM interface configuration.

The Sales Hub Professional tier is priced at $360 per month and allows up to 5 paid users. It includes features such as advanced lead management tools, automation workflows, and email tracking.

Service Hub Starter, Professional, Enterprise

The Service Hub Starter tier is priced at $20 monthly ($18 monthly for annual subscriptions) for 1,000 contacts. Its features include basic feedback collection and ticket creation/routing.

The Professional tier is available at $360 per month and allows up to 15,000 contacts. It offers advanced contact management features, advanced ticketing features, and customer feedback surveys.

Service Hub Enterprise plan is available at $1200 monthly and gives users unlimited contacts. Its features include advanced reporting and analytics, multi-brand support, and customer experience management.

Operations Hub Starter, Professional, Enterprise

The Operations Hub Starter tier is priced at $18 per month and allows integration of up to 20 external systems. Its features include custom reports and basic dashboard metrics.

Operations Hub Professional is available at $720 per month. It offers more robust reporting features such as advanced metrics, custom dashboards, and cross-object reporting.

The Operations Hub Enterprise plan is priced at $2,000 per month and offers the most advanced reporting features. They include machine learning, predictive analytics, and multi-dimensional reporting.

CMS Hub Professional, Enterprise

The CMS Hub Professional tier is priced at $360 per month. It offers features such as 10,000 website pages, custom web traffic analytics, 30 reports per dashboard, and 25 dashboards.

CMS Hub Enterprise is available at $1200 per month. It includes features like 10,000 web pages, custom web traffic analytics, 30 reports per dashboard, and 50 dashboards.

Note : HubSpot also lets you define and track information or events unique to your business with the custom behavioral events feature. This lets you make data-backed decisions that drive growth and revenue. However, this feature is only available on the Marketing Hub Enterprise plan.

How to leverage Userpilot and HubSpot to better analyze customer journeys

The Userpilot-HubSpot integration ensures seamless data transfer between two powerful products that can drive your product marketing. Basically, you can source customer data from HubSpot and use the Userpilot platform to gather customer feedback , analyze customer behavior , and drive engagement.

Here are two ways you can leverage the complementary functionality of Userpilot and HubSpot:

Monitor in-app activity data in HubSpot for better decision-making

With the 2-way integration, HubSpot users take advantage of Userpilot’s powerful analytics functionality to pull valuable insights . The in-app data will help you understand your customers and make data-driven decisions.

With Userpilot, you can:

• Monitor feature usage (clicks, hovers, text infills).
• Track events, including custom ones.
• Track engagement with checklists , surveys, and resource center modules.

Create custom HubSpot reports and dashboards for performance tracking

The Userpilot-HubSpot integration lets HubSpot customers improve the quality of their custom reports with product and user behavior data from Userpilot. This data provides a complete picture of the needs and preferences of your customers.

Userpilot users can easily visualize their data and communicate findings to stakeholders.

From learning about your brand to purchasing a product or service, to even recommending it to someone, your customers go through an entire journey.

The customer journey analytics tool from HubSpot provides a deep understanding of your customer journey so you can build a customer experience strategy that delivers results.

Get a demo to see how you can take your customer experience strategy to the next level.

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Customer Sentiment Dashboard: Definition & Examples

A Beginner's Guide to Customer Behavior Analysis

Updated: August 18, 2022

Published: December 18, 2018

You probably know your best friends pretty well — their likes, dislikes, where they shop, why they prefer certain brands, and even what they’d buy before walking into a store.

Wouldn’t it be great to know your customers this well, too? While that goal may seem like a reach, conducting a consumer behavior analysis is a great place to start. 

In this piece, we’ll cover:

• What is Consumer Behavior?
• Factors That Affect Consumer Behavior
• Consumer Behaviors That Impact Customer Service
• What Is A Consumer Behavior Analysis? 
• How to Conduct a Consumer Behavior Analysis
• 3 Consumer Behavior Analytics Platforms

Consumer Behavior

Customer behavior refers to an individual's buying habits, including social trends, frequency patterns, and background factors influencing their decision to buy something. Businesses study customer behavior to understand their target audience and create more-enticing products and service offers.

Customer behavior doesn’t describe who is shopping in your stores but how they’re shopping in your stores. It reviews factors like shopping frequency, product preferences, and how your marketing, sales, and service offers are perceived. Understanding these details helps businesses communicate with customers in a productive and delightful way. 

There are three factors that influence customer behavior: personal, psychological, and social. Let’s dive into each type. 

Factors That Affect Customer Behavior

Personality traits.

A customer's behavior in your store is heavily influenced by their personality, background, and upbringing. Some will be jovial and outgoing, others quiet and collected, and some will fall in between. Understanding where your target audience lies in this category will be vital to understanding customer behavior. 

Psychological Responses

Psychological responses can be challenging to predict, but they play a significant role in customer behavior because someone’s response to a situation is based on perception and attitude, which can change daily. 

For example, say you got a promotion, you’re having a celebratory dinner, and your server accidentally spills a glass of water on your shirt. You might be more forgiving in this instance because you’re in a great mood and having a good day. However, if you were just fired from your job, you might be more frustrated with the situation. 

Customers can be patient and satisfied one day, but the next, they’re pressing your rep on an urgent issue. Understanding that a customer’s psychological response doesn’t represent who they are as a person can help your team defuse stressful situations and prevent potential churn. 

Social Trends

Social trends are external influencers that customers listen to, like peer recommendations, societal norms, or fads. Some of these influences can be temporary, but others can affect customers permanently. 

We’ve just gone over some examples of factors influencing customer behavior; now, let’s discuss some data-backed examples of consumer behaviors that directly impact customer service. 

Consumer Behaviors That Impact Service [New Data]

A great, real-life example of how consumer behaviors impact customer service is the ways that different audience segments prefer to get service from the businesses they purchase from. The HubSpot Blog’s 2022 Consumer Trends Report asked 1,000 consumers about their preferences and the actions they take because of them. Below we’ll discuss some of the findings. 

Gen Z reported that they prefer customer service over the phone, millennials prefer email, and Gen X prefers phone calls. Each generation has a different preference, so, depending on your audience base, you want to tailor your customer service channels to speak to the behavior of each of your audience groups. 

So, for example, if you mainly speak to Gen X, you’d want to ensure that you have more reps available to pick up the phone for troubleshooting than reps monitoring social media and checking DMs. 

Now that we've outlined customer behavior and how it impacts customer service, let's learn how to analyze it in the section below.

What Is a Customer Behavior Analysis?

A customer behavior analysis is a qualitative and quantitative observation of how customers interact with your company. You begin by segmenting customers into buyer personas based on their shared interests. Then, observe each group at their respective stage in the customer journey to see how the different personas interact with your company. 

This analysis gives insight into the variables that influence your audiences and the motives, priorities, and decision-making methods customers consider during their journey. It also helps you understand how customers feel about your company and if that perception aligns with their core values.

Why should you conduct a customer behavior analysis?

Content personalization.

A customer behavior analysis is important because now, more than ever, customers expect highly personalized content. 

In fact, a Salesforce survey of over 6,000 consumers found that 66% of them expected companies to understand their needs and expectations, and a Redpoint Global survey found that 82% of respondents expect businesses to accommodate their preferences and meet their expectations and 70% say they’re highly likely to purchase exclusively from brands that understand them and their needs. So, in brief, you’ll be ensuring you speak to customers' needs and desires, contributing to customer loyalty and retention.

Customer Value

Another key business need is the ability to predict a customer's overall value . A customer behavior analysis improves this process by identifying ideal customer characteristics. By targeting these personas, your business can attract brand-loyal customers before your competitors do.

Content Optimization

The data you get from your customer behavior analysis can be used to optimize your marketing campaigns. Not only can you narrow your focus to your most valuable segment of customers, but you can also engage them on their preferred channels. This analysis can also help you deliver content at the most effective time to make an impact. 

You’ll also get insight into where roadblocks occur for each persona, helping you increase opportunities for upselling and cross-selling .

Customer Retention

While it's important to attract loyal customers, it's just as important to retain them. Accenture reported that 49% of customers expect special recognition when they're a "good customer." Even if they like your company, these people may start to look elsewhere if you don't have a way to acknowledge them. A behavior analysis can help your team reduce this customer churn by identifying good and bad customer traits.

How to Conduct a Customer Behavior Analysis

1. segment your audience..

The first step to a customer behavior analysis is segmenting your audience . 

Key segmentation models are demographic segmentation (age, gender, etc.), psychographic segmentation (personality, values, etc.), geographic segmentation (country, town, etc.), or other things like behaviors like frequent actions and product use, preferred media channels, and online shopping habits. 

You’ll also want to identify the characteristics of customers that are the most valuable to your business. One way to do this is through an RFM analysis , which outlines how recently a customer has purchased from you and how frequently they purchase from you.

2. Identify the key benefit for each group.

Each customer persona will have a unique reason for choosing your business, and it’s imperative to identify it. Look beyond the product or service and consider the external factors influencing the customer’s buying decision. 

For example, was it a purchase of convenience? Or did they make a conscious decision to seek out your brand? How urgent was the purchase, and how much do they want to spend? Thinking about the context of customers’ needs is a great way to determine areas to improve the customer experience .

3. Allocate quantitative data.

Some resources may be more accessible than others, and it's important to derive information from both internal and external sources to ensure you get a complete picture of both micro and macro consumer trends.

From within, your company can pull stats such as blog subscription data, social media insights, and product usage reports. Secondary outlets can offer things like consumer reviews and competitor analytics. Third-party data isn't specific to one company but provides general statistics across an entire industry. Through the combination of the three, you'll have a broad scope of information to work with when analyzing customer behaviors.

4. Compare your quantitative and qualitative data.

After you've collected your data, the next step is to compare the qualitative data against the quantitative. 

To do this, go through your customer journey map using the data sets as a reference. Look at which persona bought what product, when they bought it, and where. Did they return for another visit? By comparing the two sets of data against the customer experience , you can develop a detailed understanding of your customer's journey.

Comparing data should help you identify recurring trends. Look for common roadblocks that seem to pop up at different lifecycle stages, and note any unique behaviors specific to a customer type. Circle back to your high-value customers, and acknowledge anything that stands out with their buying behaviors.

5. Apply your analysis to a campaign.

As discussed earlier, you can use your findings to optimize your content delivery. Pick the best delivery channel for each persona, and take advantage of opportunities where you can personalize the customer experience. Nurture customers throughout the entire customer journey by responding to roadblocks on time. The insights you've gained from conducting your customer behavior analysis should give you a good idea of where you can make updates to your marketing campaigns.

Before rolling out your new initiatives, use your analysis to determine what your customers will think about these changes. Customers are habitual creatures, and some will push back on change even if it's for the better. These customers tend to be more loyal to your brand, so it's imperative you don't lose them as a result. Consider different ways to introduce change to these customers, and remember to be receptive to their feedback.

6. Analyze the results.

Once you've given ample time for testing, you'll probably want to know if your changes worked. Use metrics like conversion rate, acquisition cost, and customer lifetime value to determine the effect of your updated campaigns. It's important to continuously analyze your results as new tech, politics, and events constantly influence customer needs. Revisiting your analysis frequently ensures you capture new trends in the customer's journey.

Looking for some help with conducting your analysis? Check out these platforms, which are great for analyzing customer behavior.

3 Customer Behavior Analytics Platforms

As a former HubSpot support rep, I spent the last year working closely with HubSpot's analytics platform. HubSpot's reports and CRM features provide unique insight on both customer characteristics and engagement activity. You can use its reporting tools to view web traffic for contacts, and build lists based on their engagement history. HubSpot even offers an automatic attribution function that applies characteristics or scoring attributes once a contact completes an action.

Price : Starts free; up to $3,200/mo

Source: HubSpot

2. Trifacta

Trifacta's "Wrangler" features an in-depth analysis of your customer data. The tool creates an automated visual representation to make it easy to identify trends and outliers. It then evaluates the data, and makes predictions and suggestions for where you can improve your customer experience.

Price: Starts free; variable for premium tiers

Source: Trifacta

Vertica is ideal for processing high-volume data requests coming from a range of resources. The tool takes advantage of underused servers in your data center to create a speedy and cost-effective organization of your data. This lets you upload more data on your customers without sacrificing any time. Vertica can also sync to Google and Microsoft cloud servers to ensure all data is stored in one location.

Price: Starts free; variable for premium tiers as reported by G2 Crowd

Source: Vertica

Qualitative data is crucial to your customer behavior analysis, so read about how you can better segment your customer base using customer profiling .

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A Guide to HubSpot Customer Journey Analytics

Understanding the customer journey is more critical than ever.  With the increasing number of touchpoints available to customers, businesses need to have a comprehensive understanding of how their customers interact with their brand.  With the help of data analysis tools like HubSpot Customer Journey Analytics, it's easy to gain insights that will enable them to make informed decisions and optimize their marketing strategies. 

Understanding the Digital Customer Journey

The digital customer journey is not a linear path, but rather an interconnected web of touchpoints. These touchpoints can include social media interactions, website visits, email marketing, online reviews, and more. Each touchpoint plays a crucial role in shaping the customer experience and can significantly impact purchasing decisions. By identifying the most influential touchpoints for their target audience, businesses can allocate resources effectively and prioritize efforts for maximum impact.

Omnichannel Marketing

Omnichannel marketing aims to provide a unified and consistent experience for customers, regardless of the channel or device they use to interact with the brand. This holistic approach not only ensures a seamless transition between touchpoints but also fosters customer loyalty and retention . By adopting omnichannel strategies, businesses can create a cohesive brand experience, effectively guiding customers through their journey and increasing the likelihood of conversions.

Personalization

Personalization is the key to creating meaningful and memorable experiences for customers. Leveraging data and analytics, businesses can gain valuable insights into customer behavior, preferences, and past interactions. This information can be utilized to personalize content, offers, and messaging throughout the customer journey . In a time where customers are inundated with generic marketing messages, personalization provides a competitive edge, driving engagement and brand loyalty.

Customer Journey Stages

Building brand awareness.

The initial stage of the customer journey, awareness, is where potential customers first learn about a brand, product, or service. It's essential for businesses to make a strong first impression and capture the attention of their target audience. This can be achieved through a variety of strategies, such as impactful social media campaigns, thought-provoking content marketing , or collaborations with influential figures in the industry.

During the awareness stage, storytelling plays a crucial role in creating an emotional connection with the audience. By crafting compelling narratives that align with customers' values, brands can differentiate themselves from the competition and establish a solid foundation for future engagement.

Consideration 

As customers become aware of their options, they enter the consideration stage, where they evaluate different brands and their offerings. Businesses must focus on showcasing their unique selling points and establishing credibility during this crucial phase. This can be achieved through educational content, customer testimonials, and case studies that demonstrate the value and effectiveness of the brand's products or services.

Engaging customers through interactive experiences, such as webinars or live Q&A sessions, can create a sense of community and establish the brand as an industry expert. By fostering open dialogue and providing a platform for customers to ask questions, businesses can instill trust and set themselves apart from their competitors.

Purchasing and Decision-Making

The decision stage is when customers narrow down their options and make a purchase. Ensuring a smooth and hassle-free buying experience is essential to encourage customers to complete their purchase. By addressing potential concerns or barriers, offering transparent pricing information, and providing user-friendly online purchasing platforms, businesses can streamline the decision-making process and increase conversion rates.

Incorporating social proof, such as positive reviews, ratings, and testimonials, can alleviate doubts and instill confidence in potential customers. This reinforcement of the brand's value can be a powerful driver for conversion during the decision stage.

Retention 

Customer journey analysis should not end at the purchase stage. Building long-lasting relationships with customers is vital for business success, and this can be achieved through exceptional post-purchase support, personalized recommendations, and loyalty programs. By prioritizing customer satisfaction and exceeding expectations, brands can transform first-time customers into loyal brand advocates.

Proactive customer service, exclusive offers, and personalized communication can strengthen the bond between businesses and their customers during the retention stage. This ongoing commitment to providing value and exceeding customer expectations is key to fostering loyalty and securing long-term business growth.

Customer Journey Analysis with HubSpot

By leveraging HubSpot 's powerful tools, organizations can transform their customer journey analysis, creating personalized experiences and driving sustainable growth.

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Data Collection

Effective customer journey analysis begins with comprehensive data collection from various sources. This includes gathering information from website interactions, social media engagements, email campaigns, and offline interactions. By capturing data from multiple touchpoints, businesses can create a holistic view of their customers' behaviors, preferences, and pain points.

Incorporating web analytics, CRM systems, and marketing automation platforms is crucial for in-depth data collection. This ensures that no valuable information is overlooked, providing businesses with a solid foundation for their analysis.

Data Integration

HubSpot's integration capabilities enable businesses to consolidate data from different sources, eliminating data silos and creating a unified view of the customer journey. This allows organizations to understand how each touchpoint contributes to the overall customer experience. By connecting the dots, businesses can pinpoint areas for improvement and optimize their strategies for maximum impact.

HubSpot's ability to unify data from various channels allows businesses to track customer interactions across multiple platforms. This holistic approach ensures that businesses can effectively engage with their audience, regardless of the channel they prefer.

Data Analysis

In the data analysis phase, businesses can apply advanced techniques like segmentation and attribution modeling to uncover actionable insights. Segmenting customers based on their behaviors, preferences, and demographics helps identify specific target groups and tailor marketing efforts to their unique needs.

Attribution modeling enables businesses to understand the impact of each touchpoint on the customer journey. This allows for accurate allocation of marketing resources and optimization of the overall customer experience. By leveraging HubSpot's robust analytics tools, businesses can uncover the most effective channels and tactics for driving conversions and growth.

Optimize and Refine Strategies

With the insights from the data analysis phase, businesses can implement targeted marketing campaigns that resonate with specific customer segments. By continuously monitoring key metrics and conducting A/B testing , organizations can optimize their campaigns.

HubSpot Customer Journey Analytics also enables businesses to improve customer retention by identifying areas for improvement in post-purchase support. This approach allows for the creation of proactive customer retention strategies, such as personalized recommendations and loyalty programs.

Summing Up HubSpot Customer Journey Analytics

HubSpot Customer Journey Analytics provides businesses with the tools and insights they need to understand their customers on a deeper level. By following the steps of data collection, integration, analysis, and actionable insights, companies can optimize their marketing strategies and deliver exceptional experiences that drive engagement and conversions. 

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Exploring the New Customer Journey Analytics Tools in HubSpot

The announcement of customer journey analytics reporting at #INBOUND22 set the HubSpot LinkedIn community on fire. 

Since then, it's only gotten more popular as HubSpot users continue to find clever use cases for the tool and HubSpot delivers additional functionality. 

The customer journey analytics tool is based off of a type of visualization called a sankey diagram . Generally, it's used   to depict a flow from one set of values to another . In the context of HubSpot Marketing Hub, it's used to depict the flow and performance of connected marketing efforts. 

Or, in the words of HubSpot: this type of reporting allows you to "view the impact of every interaction a contact has with your business. With a journey report, you can find out which touchpoints work best for attracting customers."

Pretty cool, right? Let's explore how to use the customer journey analytics tool in HubSpot. 

Please note that in this post, we'll cover reporting as it relates to the Journey Analytics tool. You can learn more about the general HubSpot reporting tools here .

Hey, LinkedIn, I had a free hour today. So I used some of my education, marketing time that we have at Remotish to take a peek at Journey Analytics, which is the new beta that HubSpot just released coming out of INBOUND 22. It made a lot of noise at INBOUND, a lot of people are really excited about this tool. Kind of have early access to it and information about this. So we knew this was coming down the pipeline on HubSpot’s roadmap. And it's definitely been something that I've been interested in and wanting to get my hands on, but I just hadn't had a point or reason to up to this point for any of my clients.

So I took a stab at it today and cracked open the reporting tool and took a look at it. And I immediately just started to play around with some of the use cases that I would, you know, see this as a useful benefit to track a customer's journey or contact’s journey through. And definitely still learning about this tool. So I don't consider myself an expert in it by any means yet but looking to put my learnings and kind of what I'm thinking about for this tool I'm so open, get some feedback from LinkedIn and see how you guys are using it. And if you've even taken a look at it yet.

So I think this tool is really cool from like a macro perspective, how many leads are coming in? How many of those are converting into MQL, SQL? And then from there, how many of those are converting into opportunities, customers, evangelists, so forth, kind of, you know, the traditional funnel reporting that you get out of HubSpot, like you can do that in a lot of ways with this tool that expands beyond the traditional funnel reports that you would get in HubSpot, really looking at either how they've made it through their lifecycle stage or through the deal stages, is how that funnel traditionally operates.

But this allows you to now create new funnel reports from a macro perspective, to see how those breakdowns are occurring. And now through these different chart types, especially the Sankey chart, you can actually see the journey in the movement and how that relates to one another as they make it through that journey. So from a macro perspective, it's interesting. And I think there's a lot of creative freedom that this tool opens up. But where I think it really gets powerful is from a micro perspective. We've just launched this campaign, we just launched this process. And it's a really important thing for us to continue to monitor how our contacts are moving through this flow. So we're going to build out this journey analytics report for that specific flow. So I think of this tool being really powerful for going into, you know, specific things that you built out, and trying to see how that journey, essentially, is playing out across your assets.

So there's all types of options over here. You have your lifecycle stage, and then you have all the different marketing assets, you have in HubSpot, the payments tool, I think that's super interesting. And then you have some of the sales options as well. So you have your sales emails, which are your one on ones. And then you have your sequences, which are your automated, kind of drip campaigns. And you can also pull in web pages and custom behavioral events as well. So all super cool options here.

Immediately my marketing ops brain turns on, and I want to go into a portal and start playing around with what this looks like in terms of a process that I've just launched. So this is for one of the private gated websites that we've recently launched.

And here, what you're looking at is the form submissions. And one of the cool things that you can do is that you can break this down by ID, so you can get your form ID. And you can actually filter by that. How do you go about getting a form ID would be you go into your form. Thanks, Camille, for this tip. And then you go into embed that form. And then in here, you have your portal ID and your form ID, right. So when you copy and paste this code, you actually can't copy and paste it straight from here. So you have to copy it, paste it into some kind of editor and then grab the code out of here, ID out of there. And you can come in here and paste it.

Another thing that you can do is you can export all of your forms, if you want to, you can select however many forms, then you can export them, and then you can grab them all at once and bring them into here. So that's how you would essentially look at a form ID and you can filter down by that.

You can also filter down based on your emails that are delivered. So this I'm pulling the email campaign ID, make sure to use campaign and not content. And where you're gonna get that code is coming to one of your emails. See details. I'm not sure why all of these have two internal HubSpot IDs. The other quarter I was looking at only had one but you can grab those there. You can pull those over and you can use that for your email campaign ID. So for example, if you had just recently launched an entire campaign, you'll go into the campaign's tool, open up every single one of those emails individually. Pull those all out and add them here. I'm hoping HubSpot gets this filtering option a little bit better. I have a lot of experience in HubSpot, and it took me a while to figure out how to grab the form ID and the email can't campaign ID. It's not intuitive in any way. So hopefully they'll be able to add the option to filter so that this can be easier from a user experience perspective.

From that point, this particular flow I'm looking at somebody filled out a registration form that fires off the transactional email where they are delivered the email that allows them to sign up or register, which is on a systems page, it's gated, and you can only get there through that email being delivered. They don't want to know for all the emails that were delivered, how many of those were opened, and then how many of the contacts clicked a link in that email. One of the really interesting things that you can do and it kind of messes with your brain a little bit is you can add this step, make this step optional. So if I took this away, and I refresh the report, we see that it's going to, now that everything is required, they must make it through every step of that flow in order to reach the end, right. So we can see how they're tracking throughout that journey all the way down to the end.

But when you turn on make step optional, this is when you can kind of see all the different paths that somebody could take, and how they're finding their way to the end. And this is where it gets really interesting is like breaking it down by making different steps optional. And looking at the journey analytics, and then seeing what insights you can take out of it obviously becomes very complex. At this point, you kind of have to, like one of the things I'm having an issue seeing is like, understanding what this particular report is 372 contacts, went from email delivered to email open. And then 247 contacts went from email delivered to clicked links in email without opening the email, which logically that doesn't make sense, right? What I'm thinking is happening here is there's something with the privacy laws with the way that email providers are now reporting on opens, that's restricting some of the contacts from being accessible, most likely, these contacts have Apple. That's what I'm thinking, also, this tools and data. So it's not perfect either. But I can take that, make this step optional. And it becomes a very clear stream from start to finish. But I want to have an entire picture. And my nice little abstract. So I like to see things like this and go dig in and try to figure out why exactly it looks like this. But all really interesting things findings.

And then obviously, if you wanted to, you could see which of these became opportunities. And which of these became customers, right, because once they gain access to this, this gated portal that then transitions into them asking for free trials and things like that demo requests, which then transitions into, you know, actual opportunities and, and closed WON deals and HubSpot customers.

And also a couple other really cool things. No, I'm not sure this one's too cool. But you can only have up to a 30 day range for your days, which, you know, it threw me off at first, because I wanted to set this all time like I like to look at data from an all time perspective or like a quarterly perspective. But this limits you to a 30 day, which makes sense, because this is a lot of data for the report to pool and analyze. But you are limited by that. And maybe one day that'll change. But for now, it's limited to 30.

You can also sort by a property or list, which is really cool. So for example, if I wanted to look exclusively at the contacts who signed up for that dated back end, I have a list for that. And I can pull that list. So you can add that in as filter criteria, which is really cool as well. That's really kind of all the interesting thing, I think this is actually really cool.

That's the ability to see your total conversion, like 90% of the people 666 filtered in some weird number. And then 605 actually clicked the link in the email. So we know we have for people who have signed up and filled out that registration form, we know we have about a 90% conversion on this 91% conversion rate, which is amazing. And that it's really interesting to see the time that it takes for a contact to make it between these different steps, right. So here, it doesn't really make sense. But when you're looking at form submissions to the email being delivered, one of the things with this gated private content is that the first registration email from the time this form is submitted to contact us to make it into these different forms, those forms then control access to the page and fire off the registration email. One of the things that we realized through testing was that you know, abut to get cut off 10 minutes. So I'll make a part two.

The interesting thing that we found while going through the testing process was that it takes about five plus minutes for that registration email to deliver. So one of the things that I can see that verifies that is that on average, it's taking about 10 minutes for that email to actually deliver. And it's taken about an hour, a little, you know, an hour and some change, for the context to open it. And from open that's really interesting from open to click link in emails, taking the contacts 30 minutes on average. So I would imagine that they just open it. I'm not really sure what's happening there.

Yeah, it's just interesting to be able to dig deep into these kinds of analytics so interested to hear what your experience has been with this tool thus far. Where do you think it shines? Where do you think there's limitations? And yeah, I'm really interested to hear HubSpot feedback or the HubSpot ecosystem and community everybody on LinkedIn so, so longer video I appreciate everybody who stuck around to the end and please drop all your thoughts in the comments below. Thank you very much and I will talk to you soon!

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How to create customer journey reports in HubSpot

Sam Banks, our Technical Digital Strategist at Fuelius, explains how to create customer journey reports, watch the video or follow the guide below...

Hub: Marketing Difficulty: Medium Tier: Enterprise Within this article, we will be going through the newly released customer journey analytics. This was a super cool update that came out in inbound 2022, and essentially what this allows you to do is take the visualisations of Google Analytics and mix that with the simplicity of the HubSpot report builder. What this will allow you to do is create visualisations on your overall marketing journey and how context flows through that actual journey and where your volume is, but more importantly, where your drop-offs are as well. Being able to really look at your journey from a high level and looking at where you can optimise and improve because again, HubSpot gives you that platform of all those tools, with those native functions. But, being able to see where the quick wins are and where you can really optimise is where the value of the platform lies. Let's get into it.

Create a report

Conversion elements, the journey, exporting data, saving your customer journey.

Where you want to be heading is in HubSpot, under reports. You can see each time you go into analytics tools, it's prompting you that Customer Journey reports have just launched. This won't be here forever, so if you go to reports and then reports once more, it will take you to the overall reporting library. From here, if you go to create a report, you will see that Customer Journey reports are now actioned on the screen. If you select that, what you'll actually see is you can now start to build journey analytics based on the visualisations you want to build. So, down the left-hand side, there are certain touch points which you may want to actually build onto your visualisation. You could do it on life cycle stages and it will start to show how life cycle stages interact with more soft elements of the marketing journey. Or, you could just create a general funnel, such as page views to form submissions. Scroll down to where it says web pages, and drag page visitors as your first touchpoint on our journey analytics.

Then, you will start to build in conversion elements, for example, looking at how many people viewed a form and then how many people submitted a form. Then what you want to do following that is looking at under life cycle stages, how many marketing-qualified leads came from that? So, as you can see, you can do a maximum of seven as of right now at the time of the above recording, and you can then select the visualisation, as well as the date range.

As of October 2022, you can only do the last 30 days of data that may be subject to change in the future. But, if you do the past 30 days, that will give a holistic overview and what you can then do is press run report. As you can see, HubSpot then starts to build your report on the right-hand side where you can see its refreshing information. It may take a minute or so, just as it collects the data. As you can see, it's now building a contact funnel of the last 30 days of the different touch points you have built in your journey. So you can see if you hover over it, in the video example 66 contacts, visited pages in the last 30 days. Of those 66, only 42 looked at a form. So, that's 42 individuals, not 42 form views. Don't get that mixed up. And then only 33 of those contacts went on to do a form submission. Then what you can do is look at how many of those contacts were either marketing-qualified leads, or became marketing-qualified leads.

What you're quickly doing is seeing a bit of a waterfall and how that transcends down the journey. So, you can see overall the total conversion of that path is 33.33%, whereas, the average time to conversion is 31.5 hours. So, you will know that when you are trying to push people down the journey, it takes an average of 30 hours between the stages for someone to do that, for the entirety of the journey. What you can look at, if you are looking to do this and you have a lead time or a deadline that you are working towards, you have to allow for 30 hours for someone to go from step one through the funnel of what you have just built. If you scroll down, you can see a table element. So, you can see that you've got the next step conversion, how many conversions happen there? So again, it's building on the fundamentals of funnel reporting that HubFuel had out of the box as well.

You can export this data, which will allow you to export all this to a table or an Excel or CSV manner. What you should do is call this customer journey, pages visited forms, to MQLs. You can then save that report, like a normal report and add it to an existing dashboard. Alternatively, what you can do is whenever you've built your touchpoints, you can add filters. You could say that it's only on a particular page, so only certain URLs you want to track on this. Maybe on forms, it's certain forms or maybe on the marketing qualified leads, you just want to track marketing qualified leads. The really cool thing about this is funnel reporting up to now has been quite formulaic in how it's laid out, so it's standardised. You can actually use this in tandem with custom behavioural events, which Fuelius has done a video on . But essentially you can create custom events, like custom goals in Google Analytics and track micro goals within your journey, not just hard conversion points as well.

So, from there you would just press save, add to the dashboard, select your dashboard, and then from there you would save it. That's how to build a customer journey in HubSpot. Again, super easy to do. You have completed it there in six minutes and it's given us some really insightful data. Everything as standard is interactive, so once it's on the dashboard, you'll be able to click in and see the contacts, and also export that data going forward. Are you now ready to jump in? It is in beta at the moment, so see what you can do with it. Check out all of that granular data you probably didn't have access to beforehand and let's see what you can build with Journey Analytics in HubSpot.

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Omnichannel Customer Journey Mapping: The Ultimate Guide

Kate Parish

In today’s digital era, businesses need to ensure seamless customer experiences across all channels. Omnichannel customer journey mapping is a crucial tool for reaching this objective. Businesses may uncover pain areas, ensure better interactions, produce a consistent customer experience, decrease the abandoned shopping carts rate, and improve other KPIs by recognizing every touchpoint in the customer journey.

In this comprehensive guide, we’ll discuss the significance of omnichannel customer journey mapping and offer a step-by-step process for making one. We’ll provide you with the knowledge and skills business owners and marketing specialists require to improve the customer experience and raise satisfaction.

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Omnichannel customer journey maps explained.

An omnichannel customer journey map visually depicts a customer’s interactions with a brand across all touchpoints, channels, and devices. It presents a comprehensive picture of the customer journey, taking into account both online and offline encounters and emphasizing the possibilities, challenges, and crucial moments that might have an influence on customer satisfaction .

Understanding your potential lead or customer will help you drop the rate of  abandoned shopping carts and increase the number of valuable leads.

To create an efficient omnichannel customer journey map, businesses need to collect information on consumer interactions across all channels, including social media, websites, mobile applications, email, and in-store encounters. This data has to be thoroughly examined to identify recurring trends and patterns that can assist in extensive map creation.

The map should be done with the customer’s needs, preferences, and habits in mind. All the stages of the customer journey, from awareness to loyalty, should be considered, and important touchpoints that might affect the customer experience should be identified.

Once the map has been made, it may be utilized to pinpoint problem areas and establish plans for enhancing the client experience. Businesses may use the map, for instance, to identify the precise touchpoints where a client is having trouble making an online purchase and come up with ways to streamline the procedure.

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Why should you adhere to a customer journey omnichannel model.

By offering a smooth and customized consumer experience across all channels, the omnichannel model may help companies stay competitive in today’s digital environment. Here are some further arguments in favor of using the omnichannel strategy.

• Improved customer experience: Businesses may offer a smooth customer experience across all channels, including social media, email, chat, phone, and in-store, by employing an omnichannel approach. This might raise loyalty and boost customer satisfaction.
• Better engagement: an omnichannel strategy allows organizations to interact with consumers at every touchpoint, resulting in increased possibilities for contact and the development of stronger relationships.
• Higher conversion rates: Companies may boost conversion rates and lower customer turnover by giving customers a unified, tailored experience across all channels.
• Better data insights: By using an omnichannel strategy, organizations may gather data from many sources and better understand the behavior, preferences, and pain points of their customers. This can enhance overall business performance and provide information for future marketing tactics.
• Enhanced operational effectiveness: By integrating data, procedures, and technology across all channels, an omnichannel strategy may assist companies in streamlining their operations and lowering costs.

Omnichannel Customer Journey Mapping Step-By-Step

Finding your major target customer categories and channels is generally the first step in the omnichannel customer journey mapping process. Determine the stages of the journey, which may include awareness, deliberation, purchase, post-purchase, and advocacy. Consider the exact areas you want to concentrate on and the precise results you wish to attain. This will keep you on task and help you maintain your attention. Other steps of the omnichannel journey mapping process are the following:

Identifying the Touchpoints and Micro-Conversions

Determine little actions that help website visitors achieve a bigger objective (like making a purchase). Micro-conversions are potent predictors of user engagement, purchase intent, and sales funnel performance, even if they often do not contribute to a website’s total conversion rate.

List all the touchpoints where customers may interact with your brand for each channel. Examples of touchpoints include a website visit, email opening, placing an order, getting a confirmation message, and other actions. Sort each touchpoint according to the phase of the customer journey it takes place in. For instance, a confirmation letter serves as a post-purchase touchpoint, whereas an email newsletter is an awareness touchpoint.

Then evaluate each touchpoint based on how well it satisfies the requirements and expectations of the consumer. Determine the shortcomings of the touchpoints and possibilities to enhance the customer experience.

Gathering Customer Data

Gather information on consumer behavior and input from all online and offline touchpoints, including social media, email, phone, in-store, and chatbots. After gathering information from each touchpoint, arrange it in a way it is simple to interpret and visualize. Spreadsheets and customer journey mapping software are tools you may use to do this. Analyze the obtained data to find patterns, gaps, and pain points throughout the customer journey.

Creating Personas

Based on the data analysis, create customer personas that depict the various client base groups. Analyze the patterns in the information you have gathered. Group your consumers according to any shared traits they may have.

Once you have determined the traits that each group shares, make up fake customer profiles to represent each one. Give each persona a name, age, occupation, list of hobbies, and other pertinent details. Make the identities as specific as you can.

Use your established personas to guide your product development and marketing efforts. Ask yourself questions like “How would this persona react to this product?” “What channels would this persona use to find information?” or “What drives this persona to make a purchase?”

Focus on the user  – before starting your campaign, ensure that the content reflects your potential clients’ needs.

Identifying Pain Points and Opportunities

Examine the customer journey map to find problems, obstacles, and areas that may be improved. Keep an eye out for points in the customer journey where your consumers are having trouble, running into roadblocks, or getting frustrated. The product characteristics, customer service, or delivery timeframes may be the source of these problems.

Look for opportunities to improve the customer experience. These possibilities can involve delivering tailored advice, enhancing communication, or providing further services.

Prioritize the discovered opportunities and pain points in accordance with how they will affect your company’s objectives and the client experience.

Implementing Changes and Monitoring Progress

You’ll need to create a plan to improve all the weak points, solve the problems customers face, and use all the opportunities. You can use a template action plan to get started if necessary. To ensure that your customer journey mapping and action plan stays applicable and efficient in achieving your company objectives, continually examine and update it.

Customer Journey Mapping Best Practices

Understanding the mapping process is crucial, but looking for additional solutions is still imperative to make the process easier and more efficient. Here are some valuable tips worth paying attention to.

Employ the Relevant Tools

Use digital technologies to streamline the omnichannel customer journey mapping process. Here are a few examples:

• Customer Journey Mapping Software: These products make planning out customer journeys simpler and more logical by offering drag-and-drop interfaces, pre-built templates, and other capabilities. Software for charting the customer journey includes Touchpoint Dashboard, Smaply, and CX Journey.
• Analytics Tools: Data regarding consumer behavior and interactions across many channels may be gathered using analytics tools. When utilized to identify pain points and potential improvement areas, these tools can offer insights into how customers interact with a company at various stages of their journey. Google Analytics, Mixpanel, and Kissmetrics are a few well-known analytics programs.
• CRM Systems: To keep track of client interactions across various channels and touchpoints, customer relationship management (CRM) systems are utilized. Such tools help personalize customer interactions by gathering data on consumer preferences, previous purchases, and other important data points. Among the popular CRM systems are Salesforce, HubSpot, and Zoho.
• Social media listening: Such technologies may be used to track what clients say about a company on social media platforms. Businesses may use this to pinpoint areas where their customer experience could be enhanced and respond instantly to consumer complaints and feedback. Sprout Social, Brandwatch, and Hootsuite are a few known social media listening apps.
• User testing: Utilizing testing technologies, businesses may learn from actual customers about their interactions with their goods and services. Surveys, focus groups, and other kinds of user testing might fall under this category. User testing may offer insightful information on how customers interact with a company through various channels and touchpoints. Optimal Workshop, UserTesting, and UsabilityHub are well-liked user-testing software programs.

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Integration and automation tools will optimize your workflow and make it easier to manage data from various sources in one place.

Always Ask for a Customer Feedback

Your decision-making process should be guided and informed by customer feedback if you want to innovate and make improvements to your product or service. It brings wonderful possibilities that can aid in enhancing the omnichannel consumer experience.

Providing customers with a simple option of leaving feedback is essential for exceptional customer service. Thanks to the omnichannel strategy, brands can interact with customers through any channel and get feedback at each point of contact. There are several ways to get client feedback, including through websites, social media, emails, in-app surveys, and reviews. The information obtained will help you keep your strategy flawless.

Offer Self Service

Providing customers with self-service choices is another lucrative strategy, capable of enhancing the whole brand experience. One of the most crucial aspects of the customer experience is reaction speed. Customers need prompt responses to their inquiries. Through self-service portals, they may instantly access information, which also helps businesses save time and resources. Businesses can provide how-to videos, manuals, and tutorials to assist consumers in resolving their issues on their own.

Finally, omnichannel customer journey mapping is crucial for companies to comprehend customers’ experiences across all touchpoints and enhance their journey. Businesses may uncover issues and opportunities for optimization and customize their marketing strategies by developing a comprehensive perspective of the customer’s interactions.

In contrast to organizations with weak omnichannel strategies, which only keep 33% of their customers , companies with effective omnichannel customer engagement strategies have an average of 89% client retention. These figures show what a big difference omnichannel customer journey mapping can make to a company’s bottom line.

Businesses may enhance customer experience, better understand consumer wants and preferences, and ultimately increase revenue by utilizing omnichannel customer journey mapping.

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What is predictive analytics?

P redictive analytics is the use of data and modeling to predict the likelihood of future outcomes based on the historical record. Machine learning algorithms can be used to analyze large quantities of data and predict outcomes at speed.

Predictive analytics can be used in almost any field, from climate change to sports. In marketing, they are typically used to predict things like customer behavior, propensity to convert, propensity to churn and campaign performance. The data analyzed can include website and app engagement, customer sentiment and social media activity, as well as contextual data like location and even weather.

Standard (or “descriptive”) analytics seeks to understand what has happened in the past, e.g. “How did our email campaign perform with a specific audience segment?” Predictive analytics uses past data to answer questions about the future, e.g. “How will this type of email campaign perform with this type of audience?”

Predictive analytics

Predictive analytics has a long history. Decades ago, computers were used to analyze weather data in order to make forecasts, for example. Financial institutions have long used signals like credit history to predict the security of loans.

Modern predictive analytics developed as computing power increased and it became possible to analyze ever-larger quantities of data. The availability of data exploded, of course, along with the internet, and the number of channels that are sources of data continues to grow.

The predictive analytics solutions market has grown steadily over the past 10 years.

Predictive models

There are many types of models used in predictive analytics. Here are some of the more common.

Classification models. This model puts data into categories determined by the user’s criteria. A basic tool, it can give yes/no answers on the likelihood of an event occurring ( logistic regression ). A more elaborate form can offer binary answers to a series of related queries ( decision tree ). More complex but popular with data scientists is a combination of several decision trees ( random forest ).

Clustering models. Clustering assigns data to categories based on data characteristics. Marketing-related examples might include demographics, sentiment or purchasing behavior. A simple example is using historic product interest among a group of customers to predict future product interest.

Outliers models. These models identify “outliers” in the data sample. This can be used to identify abnormal and perhaps problematic events or behaviors such as fraudulent credit card transactions, building a predictive model to identify similar events in the future.

Time series models. These models use data points from a historic time period to forecast the likelihood of events in a different time period. Another simple example: A railroad might analyze data about signal failures last year to predict signal failures this year.

Dig deeper: The power of predictive analytics: Is the future now?

Predictive analytics in marketing

Here are some common examples of the use of predictive analytics in marketing.

Predictive lead scoring. Data about past customer journeys and conversion rates can be used to predict the likelihood of a prospect converting (and the likely time to conversion).

Churn predictions. Similarly, data about customers that have previously churned can be used to estimate the propensity of current customers to churn.

Content and product recommendations. Rather than surfacing content a marketing team believes to be high quality, or products a marketing team wishes to boost, predictive analytics can be used to identify the content most likely to engage certain audience segments (or, at a sophisticated level, specific users) and products most likely to be of interest.

Predictive personalization. Beyond just content and product recommendations, predictive analytics can be used to forecast “ next best actions ” across the full range of the customer experience. Artificial intelligence plays a key role here because of the scale of the data to be analyzed and the obvious desirability of executing the next best action while it is still relevant.

Dig deeper: Why you should add predictive modeling to your marketing mix

Predictive analytics solutions

Many vendors offer predictive capabilities, often as part of more general marketing analytics and performance or attribution offerings. Software review site G2 identifies more than 200 of them. Here are some of the high profile solutions in the space:

Adobe Analytics. Part of Adobe Experience Cloud, this solution uses Adobe’s Sensei AI capabilities to deliver predictive insights across data in the various cloud applications.

Google Analytics 4. GA4 supports several predictive metrics including purchase probability, churn probability and revenue prediction. It also allows the creation of “predictive audiences” based on a predictive metric.

HubSpot . HubSpot’s main focus in on predictive lead scoring (see above) and predictive sales analytics.

Oracle Analytics. Oracle has proprietary predictive analytics models available in Oracle Database, Oracle Autonomous Data Warehouse, or Oracle Cloud Infrastructure.

Pega . Pega has made next-best-actions analytics central to its CRM offering, claiming to make “real-time decisioning” possible by predicting the next best stage of the customer journey.

Salesforce CRM Analytics . Formerly Tableau CRM, formerly Einstein Analytics, this is a set of tools that includes predictive analytics capabilities leveraging Salesforce’s Einstein AI.

The post What is predictive analytics? appeared first on MarTech .

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9 Chatbot builders to enhance your customer support

Written by by Phoebe Lown

Published on  April 17, 2024

Reading time  7 minutes

Chatbots are strategic assets that enhance your customer care and marketing strategies . The technology has come a long way from being simply rules-based to offering features like artificial intelligence (AI) enabled automation and personalized interaction.

Integrating chatbots can transform your customer relations by automating responses to common queries and collecting feedback, freeing your team to focus on more complex issues. These bots boost engagement by providing 24/7 support, making businesses constantly accessible. They also streamline the customer journey with personalized assistance, improving customer satisfaction and reducing costs.

But where do you start with building a chatbot?

This article will dive into all the details about chatbot builders and explore their features. We’ll also compare some of the leading platforms in the market so you’re equipped to select the best solution for optimizing your customer connections.

Table of contents:

What is a chatbot builder?

6 features to look for in a chatbot builder, 9 chatbot building tools to boost efficiency.

A chatbot builder is software that helps you create automated messaging with customers without extensive coding knowledge. These builders offer a user-friendly interface with customizable templates and network integrations.

A user-friendly chatbot builder enables brands to design chatbots that precisely meet their requirements. It helps you engage with customers, answer inquiries and perform automated tasks.

When choosing a chatbot builder, some features will be more valuable than others depending on your business needs and how you want it to interact with customers and integrate into your marketing strategy . Here are a few to consider.

Ease of use

The best chatbot builders are designed to be user-friendly. They should offer a straightforward, intuitive interface that enables you to build and customize your chatbot without extensive technical expertise. Look for platforms that provide drag-and-drop functionality, pre-built templates and clear onboarding. Your team should be able to efficiently create, deploy and manage chatbots so they can focus on improving the user experience rather than navigating complex software.

Advanced natural language processing (NLP) capabilities

NLP capabilities like text analysis help the chatbot process and interpret human language and understand a comment contextually. NLP works synergistically with functions such as machine learning algorithms and predictive analytics. These technologies enable the bot to continuously learn from user interactions, improving its ability to provide accurate responses and anticipate user needs over time.

Multi-platform integration

Customers engage with businesses online in many ways, such as through messaging apps, social media and websites. To deliver omnipresent customer support, your chatbot needs to meet your customers where they are. Multi-platform integration ensures that your chatbot provides a consistent and cohesive experience, regardless of where the interaction starts.

Analytics and reporting

Understanding how users interact with your chatbot and identifying areas for improvement helps you optimize your chatbot performance. A good chatbot builder should offer comprehensive social media analytics and social media reporting too ls that track performance metrics like engagement rates, user satisfaction and resolution rates. These insights let you refine your chatbot’s responses, adjust functionality and enhance effectiveness.

Customization and personalization

Customization and personalization are important in creating chatbots that match your brand’s voice. A high-quality chatbot builder should offer customization options, covering everything from the chatbot’s appearance and conversation style to its workflows and responses. With personalization capabilities, your chatbot can accurately represent your brand while providing customized user experiences, enhancing interactions and making them more productive and engaging.

 Scalability and performance

As your business grows, your chatbot should be able to scale accordingly. Scalability ensures that your chatbot handles increasing customer interactions without compromising performance. A chatbot builder should also offer reliable uptime and fast response times so users receive timely and efficient assistance. 

1. Sprout Social 

Sprout Social is a social media management platform with an integrated chatbot builder. Sprout’s Bot Builder is designed for businesses that aim to automate and personalize customer care on social media .

Best for: Overall chatbot builder 

Highlights:

• Integrated with Sprout’s comprehensive social media management tools
• Easy to design chatbots with automated conversational workflows for X (formerly known as Twitter) Direct Messages and Facebook Private Messages
• Advanced targeting options for personalized messaging
• Live preview feature to test chatbot interactions in real-time
• Pre-configured chatbot templates

Building chatbots with Sprout is straightforward, with blank and preconfigured templates, making it easy to develop chatbots that align with your brand voice and customer service goals.

Its customizable chatbot appearances and configurable conversational components, like Welcome Messages, Quick Replies and Auto-Responses, enhance user engagement and help streamline customer service .

Sprout’s live preview feature lets you test and tweak chatbot interactions, ensuring an optimal user experience. Once live, you can seamlessly monitor customer conversations within Sprout’s inbox along with your other social media engagement, facilitating a smooth and consistent customer experience across social channels.

Watch this video to see how quickly you can use Sprout to build, deploy and manage chatbot conversations within one platform.

2. HubSpot 

HubSpot is a leader in marketing and sales platforms, offering a versatile chatbot builder as part of its Service Hub product.

Best for: Integration with other HubSpot services

• Free basic plan, users can access a powerful AI chatbot builder at no initial cost
• Handles tasks from qualifying leads to booking meetings and collecting feedback
• Integrates with HubSpot’s suite of marketing and sales tools

HubSpot’s chatbot creator enables integration with marketing and sales platforms and is good for tasks like lead qualification, scheduling meetings, handling FAQs and feedback collection, all within HubSpot’s ecosystem.

3. Botpress 

Botpress is known for its conversational AI capabilities and user-friendly platform. It offers large language models (LLM) and generative AI, facilitating personalized and engaging chatbot experiences.

Best for: AI capabilities 

• User-friendly workflows accessible to users of any skill level
• Utilizes advanced AI for automated programming codes and productive tasks
• Available in over 100 languages

Botpress automates managing customer queries and tasks to save time and improve customer interaction quality. Its no-code approach and integration of AI and APIs make it a valuable tool for non-coders and developers, offering the freedom to experiment and innovate without upfront costs.

4. IBM Watsonx Assistant 

IBM Watsonx Assistant is known for its advanced conversational AI capabilities, which enable you to build virtual and voice assistants that offer fast, consistent and accurate customer support across any messaging platform. 

Best for: Voice interactions

• Advanced AI learning improves customer conversations for first-time issue resolution
• Can be deployed in any cloud or on-premises environment
• Knows when to seek answers from a knowledge base, ask for clarity or direct users to human agents

IBM Watsonx Assistant is an AI chatbot builder that addresses numerous customer service challenges. It reduces wait times, eliminates the need for tedious searches and enhances the customer experience by providing accurate answers. Its NLP and ML capabilities enable it to understand and respond to user queries effectively.

Wit.ai chatbot builder provides seamless integration of NLP into chatbots. It caters to technical and non-technical users.

Best for: Quick setup

• Easy-to-use interface for configuring chatbots
• Detailed API documentation
• Quick setup, requiring minimal data for effective learning
• Efficiently handles messages outside the chatbot workflow

Wit.ai is valuable for collecting contact data within conversations, enhancing user engagement without compromising the chat flow. This AI chatbot builder is a perfect fit for projects that aim to incorporate NLP features rapidly, even without in-depth AI knowledge. It simplifies adding intelligent conversational features to chatbots despite some limitations in non-text functionalities and a slight learning curve for beginners.

6. Amazon Lex

Amazon Lex offers deep learning technologies for conversational AI to improve user interactions with sophisticated, lifelike bots.

Best for: AWS ecosystem

• Utilizes the same deep learning technologies that power Amazon Alexa
• Integrates with other Amazon Web Services (AWS)
• Prebuilt dashboards with metrics such as total conversations and intent recognition rates
• One-click deployment to multiple platforms like Facebook Messenger, Slack and Twilio SMS

AWS users and developers who want to add advanced conversational AI to their applications can use Amazon Lex’s scalable model to create applications with conversational interfaces. Amazon Lex knows when to seek answers from knowledge bases, ask for clarity or direct users to human agents, enhancing the overall customer experience.

7. Manychat

Manychat offers a convenient solution for D2C brands, retail stores, non-profits, restaurants and real estate companies. It allows you to engage with customers seamlessly across various channels, including Instagram Direct Messages, Facebook Messenger, WhatsApp and SMS.

Best for: Omnichannel support

• Intuitive platform with drag-and-drop functionality and pre-made templates
• Integrates with GPT API

Use this tool to automate and improve customer communication across multiple channels. Its ease of use and social media features, like responding to post comments, along with integrations with Stripe and ConverterKit, make it an essential tool for conversational strategies.

8. Chatfuel

Chatfuel is a chatbot builder designed for freelancers and startups that focus on enhancing client interactions through social media. Using NLP, Chatfuel aims to deliver engaging conversational flows. The service provides many Messenger bot templates, enabling users to choose the best fit for their needs.

Best for: Smaller businesses and freelancers

• Chatbot templates alongside comprehensive reporting and analytics for performance monitoring
• Shared inbox for streamlined communication across multiple platforms

Chatfuel streamlines the creation and management of social media chatbots, particularly for Facebook and Instagram. Despite some limitations regarding customization and complexity, its user-friendly nature and integrations and analytics make Chatfuel a cost-effective option for businesses aiming to boost their social media engagement and automate customer interactions effectively.

Flow XO is a user-friendly chatbot builder that helps you create code-free bots. Its simple setup process allows for quick deployment across various channels.

Best for: Quick deployment 

• Standard integrations, including Stripe and Google Analytics
• Ready-to-use templates tailored for different business needs

Flow XO for Chat offers a solution for engaging customers through chatbots without coding. The platform offers a diverse range of ready-to-use templates tailored to different business needs, further expediting the bot creation process.

Build chatbots like a pro 

The right chatbot can improve your team’s efficiency and enhance customer experiences. After reviewing our list, evaluate your options thoroughly. Experimentation is key; we encourage you to test out different chatbot builders firsthand for ease of use and to discover which best aligns with your goals. 

If enhancing your social media strategy is a priority, Sprout stands out for its ability to foster genuine connections. By unifying every customer interaction in one place, your team can offer personal, positive engagement without depleting resources. You can explore Sprout and test it right away on your social media channels with a no-commitment free 30-day trial .

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