What do we mean by the customer journey? Simply put, analysing the path that the customer takes while they are navigating the site, to produce actions that benefit both the customer and their experience.
Why should we care about analysing the customer journey? Customers are at the heart of all businesses, without them, there is no business. Analytics helps us to prioritise where to assign resources and research by adding measurable numbers to customer actions. It helps us understand if we’re succeeding and if our customers are happy with the services we’re providing.
Insight and Analytics help break down some of the barriers between various functions by being a shared language that can become part of a shared culture. By agreeing defined sets of relevant metrics, we can recognise our successes and failures and learn from them, helping us work towards common goals across the whole of the customer journey. It helps us to base our actions on customer data instead of assumptions.
I’ve broken this journey into 5 stages which I’ve labelled from A-E. Not all areas of Customer Analysis fall neatly into these stages, many have elements of multiple stages feeding in and feeding back into multiple stages, including back into themselves. Reflecting this some metrics, sources, and tools will appear in multiple stages. It’s a generally adaptable approach, not a strict method.
A — Acquisition
Where do our customers come from? How do we reach them to bring them into the site? Who is our audience?
B — Behaviour
What do our customers do on the site? What do they like, what don’t they like? How do they act on our site/with our product?
C — Conversion
Are our customers performing the actions we need/want them to? Do they ‘buy’ from us?
D — Delivery
Did we give them the product they wanted? Was the experience/product fit for their purpose?
E — Engagement
How do we keep in contact with our customers? Do we listen to them as well as talk with them? Do we take actions from these conversations?
I’ll go into a bit more detail about each of the stages below, the list is supposed to be more demonstrative than exhaustive. I’ll break each stage down into:
● the meaning of the stage,
● it’s purpose,
● the likely sources and tools you’ll need for analysis,
● the metrics you’ll get from this stage
● finally, some of the kinds of actions and outcomes you can prompt from this stage.
A — Acquisition
This stage defines our initial audience, where our customers came from, not just geographically but also how they found the site. It’s designed to show how effective our marketing, promotion and out-reach is. We need to pull the most relevant customers to the right place on the site. This is about reaching our audience with a relevant message for them, at the right time.
Find out where our customers came from, which channels they used. It’s designed to answer questions such as: Do they act differently if they come through Google, an email or a shared link? Where do they arrive on the site, is it where they want to be, is it relevant? Are they coming back or is the first time we’ve seen them? Are the needs of these two groups different? How much did it cost to get this customer to our site?
· SEO — What we’ve done to our site internally to boost it in the rankings.
· Direct traffic — People who come directly to the site by bookmark or entering the address in their browser.
· Email platform — Campaigns, Newsletters, Announcements etc.
· Organic searches — Google traffic. What we’ve done to our site externally to boost it in the rankings.
· Social Media — Instagram, Facebook, Twitter
· PPC Traffic — Google ads
· Affiliates — White-label traffic, partners who we pay commission to for their traffic
· Email marketing software — MailChimp etc.
· SEO — Google Search Console, SEMRush
· Web Analytics software — Google Analytics, Adobe Analytics etc.
· PPC Analytics software — Google Ads Platform etc.
· Landing Page Analysis — Unbounce, Optimizely
· Internal data-sources — MySQL, SQL Server, hopefully, not Excel etc.
· Open Rate (OR) / Click-through (CTR) rate by campaign
· Cost per Click (CPC) / Cost per Acquisition (CPA)
· Return on Advertising Spend (ROAS)
· Affiliate traffic Analysis
· Bounce Rate
· Time on Landing Page
· Channel Mix of incoming traffic
· New / Returning Customers
· Cohort Analysis
This is about our audience, our potential customers and how we can reach them, how we can help them to discover the right product for their needs.
The Acquisition step can help to increase CPC and reduce CPA by making landing pages and email campaigns more relevant to targeted customers, this often correlates to the Bounce Rate of the Landing Pages our customers arrive at. We can also improve SEO by finding out what on our site draws traffic to our site and boosts it up the search rankings. Improving Organic traffic is how our brand is viewed, are we credible, do people know and trust us?
This is the area where we start to segment our audience, which channel did they arrive through, what was the purpose of their search that brought them to us? If they’re a first-time customer we can offer them walkthroughs, demos and other on-boarding to help them use our site. If they’re a returning customer target their experience with results based on their previous behaviour and purchases.
We can help our Affiliates and supply partners make the most of their relationship with us if we’re taking care of them and their customers, they’ll take care of us. This should always be a mutually beneficial relationship that thrives on both sides.
If we can’t attract the right people, to the right parts of our site, for the right reasons, then we are going to have trouble encouraging them to complete their journey with us and re-engaging with us in the future. A bad first experience can ruin a customers impression of a site/product in a way that can never fully be recovered from.
B — Behaviour
This is the stage that is one of the most visible. It concerns how the customer acts when they’re on our site. It’s often where UI/UX and Experimentation are most visible. It’s about how the customer interacts with the website and the various elements on the screen, making their journey as quick and painless as possible.
This is to help identify any pain-points in the customer journey, are there any parts of it that actively stop people from progressing? Do they have to go forwards and backwards between two points to find the information that they need? Are they looking at the parts of the screen that we want them to? Are there any common factors that people love / hate? This is the area where Accessibility sits, making sure that all customers can use the site.
· Web Traffic — How do customers move through the funnel and interact with the site?
· Session tracking — Aggregating how the average customer interacts with the screen
· Surveys — At some points in the journey, how do the customers feel?
· Internal Datasets — Are we tracking everything we need to?
· Event Tracking — Is everything running smoothly in the back-end?
· User Interviews/Studios — See how customers actually use the site in reality
· Accessibility testing software — Does the site conform to the relevant standards?
· Session Tracking Software — Hotjar, ClickTale etc.
· Web Tracking Software — Google Analytics, Adobe Analytics, Firebase
· Survey Software — Usablilia, Survey Monkey
· Internal Datasets — MySQL, SQL Server, Excel etc.
· Accessibility Checker — Many online versions
· Qualitative User Data — Excel or other spreadsheet, Power BI, Tableau
· Event Tracking — AppDynamics, Kibana, Google Analytics
· HEART Framework
· Funnel Progression
· Accessibility Standard
· Funnel drop-out points
· Errors or other back-end issues that may impact the customer’s journey
· Forward and Backward motion through the funnel
Behaviour is how people are acting on the site, the idea is to make the site easy to use for as many people as possible. To assist with this, we need to track pain-points — Where are people dropping out of the funnel, what are they having problems with? We can reduce the number of people having to double-back on themselves by ensuring that they can find what they need the first time they visit a page. We can see how closely they follow any of the optimal customer journeys we’ve mapped out, are they converting in the fewest possible steps without detours?
This is often where UX and CX are used, making people look at and engage with the appropriate parts of the screen. Ensuring that there’s a consistent theming across the site helps reassure the users that they’re dealing with a professional organisation that’s thinking of their needs.
Your UX team may already have their own metrics and ways of measuring behaviour that can feed into the flywheel. An example of this would be Googles’ HEART Framework for Measuring the User Experience (link to the original paper, links below to a series of Medium articles by Tomer Sharon that explain the stages)
· H — Happiness. Basic measures of Customer Satisfaction. Are our customers happy with their experience of our site?
· E — Engagement. Measures the interactions our users have with the site. How long are our customers staying?
· A — Adoption. Measures how well we attract new users. How did people find our site, is it what they were looking for?
· R — Retention. Measures how well we keep our existing users. Are we doing all we can to make their on-going experience as good as the initial one?
· T — Task Success. Ease of use metrics. How long does it take our customers to do what they want to? Can they do what they want to?
Some of the metrics suggested by this UX framework slot easily into other steps in the flywheel, others require more effort. It’s always worth trying to integrate metrics from other functions into your analysis as it gives you a wider, big-picture view of the process.
Here, we need to split our users by their intent, the journey they are intending to go on today and how we can help make it a smoother, more frictionless experience. For example, there’s usually a difference between the behaviour of people who are browsing vs people who are intending to buy, we need to encourage both kinds of behaviour as today’s browsers can be tomorrows buyers. Time of day and day of the week are also important as people have different needs at different times. Should we differentiate our content based on this or the method of delivery, if so, how?
We can have back-end site-monitoring in this step, making sure the site works for the customer’s journey, spotting and fixing errors and inconsistencies before the customer is aware that there’s an issue.
Check all the elements on the screen, we make sure that they work correctly, see which are necessary, which can be removed. We need to make sure that the customer’s options are presented cleanly and clearly to them without being too distracted or the screen too cluttered.
There’s also an opportunity to extract plenty of qualitative observations from user testing that we can’t from quantitative data. Not everything can be reduced to a simple, single number no matter how tempting this would be. People are far more complicated than that!
C — Conversion
Conversions are customers on our site performing an action that we want them to. There are two kinds of conversions Macro-conversions and micro-conversions.
Macro-conversions are the large-scale, goal of the journey while micro-conversions are the smaller steps on the way to a macro-conversion. This stage is also where the value of the conversion is taken into account. Are there ways we can increase the number of transactions or revenue per transaction by guiding the customer?
We use conversions to track whether our customers are acting as we would like them to. By measuring the effectiveness of these we can improve the customer’s progression toward the end of the funnel.
Macro-conversions: These are the metrics we’d use for KPI’s and SLA’s. This is where the money comes from, this pays our wages. This is the product or service we’re selling. These include sales, bookings, and whatever other actions ultimately provide a product or bring in revenue. A macro-conversion is traditionally the end of the customer journey. These are the kind of metrics that C-Level executives and upper management are very interested in, they tend to be revenue drivers and are usually quite simple to gather and analyse. They are often but not always financial or sales metrics.
Micro-conversions: These are the steps that cause a greater sense of buy-in and investment from our customers. These do not necessarily pay-off now but should encourage a later pay-off. This is getting people involved in their journey with us. These include actions like interacting with filters, signing up for a newsletter or searching the site. Micro-conversions can occur at any point in the funnel and do not signify the end of the journey, they are merely a staging post towards the destination.
Micro-conversions tie quite closely to the Behaviour stage, seeing how many customers interacted with something and seeing if they can be segmented further to learn any specific lessons. We use micro-conversions to find out if customers are interacting with the elements that are likely to increase the chance of a macro-conversion by smoothing the user-flow or engaging more deeply with it. We can apply the lessons from high converting traffic to lower converting audience segments and find useful commonalities between the two.
We can also use micro-conversions to drive revenue, if someone has made a macro-conversion we can offer them add-ons to increase take-up, this interaction could be a micro-conversion. We can offer them a similar product or guide them to another part of the site that might contain related content that they might enjoy.
· Email platform — Are people signing-up to from our site?
· Web Tracking Software — How are people acting within the funnel?
· Event Tracking Software — Are people triggering the events that we want them to?
· Revenue Tracking — How much money are we making from each customer?
· Internal Datasets — Are we tracking everything we need to elsewhere?
· Session Tracking Software — Can we see why people are interacting with the pages containing micro-converting events? Do they have a positive effect?
· Survey Software — Can we find out what they thought of their journey when they’ve immediately completed it?
· Email Tracking Software — MailChimp
· Revenue Tracking — Google Analytics Advanced E-commerce, Internal Tools
· Web Tracking Software — Google Analytics, Adobe Analytics etc.
· Event Tracking Software — Google Analytics, AppDynamics
· Session Tracking Software — Hotjar, ClickTale etc.
· Survey Software — Survey Monkey, Google Forms, Internal Tools
· Internal Datasets — MySQL, SQL Server etc.
· Conversion Rate (CR)
· Attachment of Extras
· Click-Through Rate (CTR)
· Time on Site, Pages Viewed, Number of Interactions (Attention/Information Economy products)
· Net Promoter Score at Confirmation Stage (NPS-C)
· Sales per Day / per Quarter / by Product
· Average Revenue Per User (ARPU)
· Average Margin per Day / per Quarter / by Product
· Filter / Search box interaction
· Logging-in to an account (LiR)
· Signing-up to a newsletter (SuR)
The conversion step is where we get our customer to perform the actions we’ve decided that are a useful part of their journey towards goals we want them to reach. These are not just related to selling them a product or service. Some industries and sectors don’t rely on selling a product, they rely on customer engagement, knowledge sharing or other top-line success metrics. In the attention economy, sign-ins, shares, time on site or pages viewed might be the high-level macro-conversions that senior management are interested in, a different way to measure revenue.
Micro-conversions can be ways to measure if we’re helping make their visit easier, encouraging them to continue their journey or increasing their commitment to the process. We can do this by increasing sign-ups to our newsletter’s, encouraging them to sign-up for, or sign-in to an account on the site. We can give them a free quote and hopefully give us a chance to re-engage with them at a later date.
We can also increase revenue per customer, increasing the amount they spend when they shop with us and increase the likelihood that they’ll buy from us in the first place. This is one of the steps where we can find underserved segments and improve their journey by using the lessons learnt from better-converting traffic. There might be something that one segment is doing that the other isn’t, could be good or bad.
This step usually has very definitely defined metrics that are straight-forward to measure and can be very persuasive in showing senior management a concrete bottom-line impact. A 10% rise in revenue is often a lot more interesting than 10% longer spent per session in most industries.
We are aiming for a smoother customer journey where the customer moves seamlessly through the funnel towards our goals for them and our business. If we’re looking for them to make a macro-conversion, such as a sale, we need to find the micro-conversions along the way to encourage them in this goal. We are looking to keep their attention and to give us a chance to re-connect with them down the road.
D — Delivery
Delivery follows-on directly from the Conversion stage, both macro and micro-conversions need a product or service delivered. The quality of these are probably the element that affects the long-term customer experience in the most significant way. This can be tricky to measure as we are quite often reliant on external sources to get our data and our feedback, some of the data may be contained within verbatim reviews on external sites. The data in this section can sometimes be subjective and therefore biased by personal feelings.
The purpose of this stage is to give the customer the product they are expecting and that they have made their way through the funnel to acquire. It must be the right product, at the right time, in the right place, of the right quality, for the right price.
The Delivery stage is where our Customer Satisfaction tends to come from. A product isn’t just a physical object or other macro-conversion, it can be an email, a live-chat or any other kind of micro-conversion. Are we providing our customers with what we promised and more importantly, is it what they really want?
This can also be used as a sign of how good the product and customer service we are providing is. These can be the hardest metrics to move because it can rely on many details that we have no personal control over i.e. did the courier deliver the package on time?
As these can be skewed by the mood of the customer at the point of delivery, the subjective nature of some of these metrics means that they can never entirely be relied upon but are still a vital source of actual customer sentiment. It’s always better to base your analysis on data rather than assumptions, even if you know that the data should be treated as more a guide than a rule.
· Customer Feedback and Reviews — Finding out how we did, what customers liked, what we can improve.
· Supplier / Partner / Affiliate Feedback — Discovering whether our partners are supplying our customers and ourselves with the product we’ve ordered.
· Account Interaction — Is the account section of our website providing any value to our customers, is it providing us with any usable data?
· Email Tracking — Making sure that our customers got the relevant email at the right time.
· Customer Service Metrics / Complaints — Finding out if our customers been in touch about our product. What can we learn from this? Has this affected their view of the company/product?
· Customer Feedback and Reviews — Internal Tools, Google Reviews, Trustpilot
· Supplier / Partner Feedback — Internal Tools, Survey Monkey, emails received MailChimp
· Account Interaction — Internal Tools
· Customer Service Metrics — Internal Dataset, Incoming contacts
· Complaints — On-site form, MailChimp
· Email Tracking — MailChimp, Internal Dataset
· Net Promoter Score — Post-Delivery (NPS-PD)
· Other results from Post-Delivery Surveys (Likelihood to re-use, Quality of Service, Quality of Product etc.)
· Repeat Rate/ARPU/CLV will sometimes fall into this area, depending on how they’re being used.
· CSAT metrics — Including the number of contacts, price per contact, the speed of resolution
· Verbatim Comments — Gives texture, use word-clouds to get general themes quickly.
· Ratings from external sites — e.g. 4.5/5 Trustpilot score, Google Reviews.
This is the step the customer will probably remember the easiest, they came to our site looking for something, they purchased it, what did we give them? Was it what they wanted? It relates very closely to parts of the Engagement step because we can’t find everything out about the delivery of our product without hearing whether our customers were satisfied with the product they’ve received.
This can highlight any issues with our suppliers, our product, even, how we’re promoting it. We rely a lot on external agencies in this step, so we have to track their performance to check that they’re performing in the way we’d like them to.
If we’re using Post-Delivery Net Promoter Score, which is not really an actionable metric, we can add more impactful questions to the same survey to gain some more valid insight as well as having aggregated top-line figures to pass up to senior stakeholders. The other questions can be targeted to specific areas of the product/service. Was it clean, was it on-time, was it useful, was it value-for-money? All of these more granular questions can help to highlight specific issues that our users are having with the final product we’ve delivered and we can then address these issues.
We can use external review sites and surveys to help boost our organic traffic as well as monitor our products and suppliers. If we have good reviews on external sites it increases the relevance and amount of ‘social proof’ that search engines look for when deciding their rankings. Survey results should always be used with caution as satisfied customers are less likely to leave feedback. This is another step that contains many subjective metrics, they are sometimes not an accurate representation of the service received, more a reflection of the customer’s mood at the time the survey was completed.
This can also be where we save money, by having a better product and better Customer Service we can reduce the cost of dealing with complaints and the number of customers contacting us by giving them less reason to contact us. We can reduce refunds and compensation by finding ways to deliver our product so that it satisfies our customer’s needs.
It can help to shape future offerings and products by finding out what was/wasn’t popular with which specific sections of our audience and use these insights to drive future product innovation. Surveys let us know what our users are looking for in the future, what they’re hoping to get rid of from the past and what could be better. We can identify pain-points caused and solved by the product, stop doing what they hate and start doing more of what they love.
E — Engagement
This is, in my opinion, the most important stage of the Analytics journey. This is where we communicate with the customer, not just talking at them but also listening to them. This stage helps a monologue become a dialogue and hopefully fosters a sense of loyalty and commitment. It’s where we can nurture a sense of community and belonging. Its where brand loyalty comes from and it’s how we expand our reach and communicate effectively.
It’s generally agreed that it costs around five times more to attract a new customer than to retain an existing customer. By fully engaging with our customers we can spend less on Acquisition cost, giving us higher ARPU or a lower CPA. We can move our customers away from expensive acquisition channels like PPC toward cheaper or free retention channels like email. It’s much better to encourage repeat custom than to have to ‘buy’ every customer, every time.
This is where we gain a better understanding of our customers and where our customer gains a better understanding of us, our product and our vision. Are we saying the right thing at the right time in the right way to the right people? Are they interested in what we’re saying and are we making a connection with them? Do we listen to what they say and vitally, are we acting upon it? Can we give them something they don’t yet know they want because we’ve paid attention to them?
This is another area where subjective opinion and personal bias can affect accurate insight, there’s much uncertainty surrounding customer engagement because people have such varied likes, dislikes, needs and desires.
Not all customers will share their opinion with us, so we must take full advantage of those that do to find the themes, the areas of friction and the pain-points in their journey and make easing these part of our planning. People are more likely to leave a response when their experience has been negative to let us know that they’re annoyed or disappointed and exactly, often passionately and in great detail, why they’re annoyed. An experience that was just “OK” but no more or less doesn’t tend to encourage engagement.
Positive comments are harder to gain insight from than negative ones. 10/10 with a comment of “Great” is a sign of a great product but unfortunately doesn’t tell us what makes them love the product. We must learn, not just from the negatives, what we shouldn’t do but, also from the positives, what did people love, can we do more of this? We can look at the product the customer used, the interactions with the site and by engagement channels and see if this is an optimal path and if we should be driving other users of this type towards this journey/product.
· Email Tracking — Finding out which emails people respond to
· Call / Contact Centre — Discovering why people needed to get in contact
· Interaction with Account — Finding out what people are doing when they log-in, is it a compelling experience
· Session Tracking — How did they engage with the elements on-screen, did it help?
· Web Tracking — Seeing how smooth their experience was.
· Event Tracking — Checking which events are being triggered and whether they help or hinder the customer.
· Survey Tracking — Finding out the issues that cause people to contact us by listening to what they’re saying.
· Qualitative Data — Looking at the themes, subtleties and nuance of customer comments.
· Email Tracking — MailChimp
· Call / Contact Centre Tools — ZenDesk, Internal Datasets
· Interaction with Account — Internal Tools, Internal Datasets
· Session Tracking — Hotjar, ClickTale
· Web Tracking — Google Analytics, Adobe Analytics, Firebase
· Event Tracking — Google Analytics, Internal Tools
· Survey Tracking — Usablilia, Survey Monkey, Internal Tools
· Qualitative Data — Manual/Visual Analysis, Word Clouds, Sentiment Analysis, NLP, Themes
· Open Rate (OR) / Click-through Rate (CTR)
· Repeat Rate (RR)
· Logged-in Rate (LiR)
· Customer Lifetime Value (CLV)
· Average Revenue per User (ARPU)
· Return on Advertising Spend (ROAS)
· Cost-per-Click (CPC)
· Cost per Acquisition (CPA)
· Incoming Channel Mix
· Frequency / Recency of visits
· Cohort Analysis
· New / Returning Customer mix
Engagement is not only how we talk to our customers, it’s also about how we listen to them. Do we act on their concerns, do we understand their preferences, are we making them feel heard? We need to move on the potential actions suggested by their feedback, whatever the source.
We can have a positive effect of engagement, commitment and retention by increasing the Logged-in Rate and the rate at which people sign-up to our promotional material. By increasing the channels and opportunities for communication and re-engagement we have a better chance of re-acquire dormant customers without starting from scratch.
By communicating effectively with our users, we can increase Word of Mouth which improves branding, awareness and sentiment, increases the mix of direct and organic traffic and drives down the cost of any paid acquisition channels we use. By decreasing our Cost Per Acquisition and Price Per Click, we can decrease our Paid Search channel Mix, increase our SEO, Email and Organic Acquisition channels.
This is a reason that the Engagement step ties in so closely with the Acquisition step.
The work of Engagement can directly lead to the creation of communities, such as forums, Facebook groups, Twitter hashtags or other forms of social sharing and proof.
Other Engagement actions that affect Acquisition are Email Tracking, by A/B testing of the subject line, time sent, or the content we can find out if we’re delivering a relevant message to our customers when they’re open to receiving it. Positive outcomes from this can be an increase in the rate that our customers make repeat purchases. We can improve the New/Returning Customer mix and increase the frequency of the visits of our returning customers.
This step can really improve our bottom line, by taking care of our customers and engaging with them we can improve our Return on Advertising Spend, Average Revenue Per User and ultimately raise our Customer Lifetime Value to new heights.
I’ve barely scratched the surface of this subject as there are many more subtleties to take into consideration e.g. do customers in different countries have a different experience, does the device type make a difference?
As you can see in the following diagram, all these stages follow-on from each other and create a ‘positive feedback flywheel’ where successes with previous stages feed into each subsequent stage. At the centre of the flywheel, you’ll notice there’s a ‘Cx’, this represents the Customer, whose experience should be at the heart of all customer analysis and all businesses. They’re speaking, it’s up to us to listen.
● Which stage is the main focus of your team?
● Which other stages are a part of your work?
● Is there a stage you prefer to focus on?
● Are there any stages where you feel less confident?
● Who are your teams’ customers?
● Who are your customers?
● What are your Key Metrics?
● How are you going to measure them?