The Anatomy of a Data-Driven Customer Buyer Journey
The customer journey can take many different forms with twists and turns that drive people to make buying decisions, but for the most part, the touchpoints are all the same: ads, website visits, landing pages, emails, SMS, retargeting ads.
There isn’t that much more to the customer journey than those touchpoints that a brand can control before purchase.
The key, though, is to understand the complete lifecycle and how different elements of your marketing stack play a role in creating experiences that help your customers on that journey to learn about your products, understand your products, consider your products, purchase your products, and come back and purchase more products.
The best brands in the world take a data-based approach to learn about their customers, their audiences and tailor and create content that speaks to them.
For many small and medium-sized businesses, the idea of collecting data about their customers is often an afterthought or doesn’t exist at all.
With recent privacy changes and future changes coming to the digital landscape, brands that don’t adopt a data-centric approach will face particular challenges.
The purpose of this guide is to provide an overview of a simplified data-driven customer journey and go into an overview of the parts and how they fit together.
Ads and organic traffic are very different. Both are important but should be used in very different ways.
Organic traffic is a result of a brand's presence, content, or mention via word of mouth, though traffic comes from all sorts of places and can include someone seeing an ad and directly typing in the address, etc.
Organic will happen on its own through targeting the right publications and getting mentions in the right groups. It’s a community play.
Ads, on the other hand, are more curious in their intent. People click on ads for any number of reasons, and some, if not most, are not completely clear.
Ads lack the built-in context of organic traffic.
So how do Ads play into the data-driven customer journey?
When you set up your ads and paid traffic, you have control over who your message reaches. You can narrow down and test different audiences, messaging, and creative.
Everything should have a process. Much like the chart above, there should be similar ones for narrowing down an audience, copy for your audience, and creative for your audience.
It is the first step of a data-driven marketing journey.
- Know your audience
- Speak to your audience
- Create creative for your audience
Know your audience
There are three major trends when it comes to ecommerce targeting paid advertising specifically focused on Facebook.
- Target generally - let Facebook find the best people for you
- Target around interests - let Facebook target people that have expressed interest in certain things
- Target around lookalike audiences - audiences that you upload into Facebook and let Facebook find similar ones
This is the first step of targeting, understanding who will work its way into your buyer journey as the journey incorporates the ad, the website, the value propositions, all the way to post-purchase.
If you’re targeting generally, it becomes harder to know who your audience is.
It's pretty much a crapshoot that relies on Facebook to send you quality traffic. This puts a lot of pressure on your ad copy and creative, with placements becoming more focused on images, there is more pressure than ever on the creative.
Target around interests
If you’re targeting around interests, you want to own the experience and personalize the traffic to your website to specifically targeted landing pages.
You won’t know enough about your audience but you can start to use zero-party data collected to build models for these.
Targeting around lookalike audiences
Targeting around lookalike audiences means you’re allowing Facebook to target people similar to the list of people that you uploaded into Facebook or a segment you connected via your ESP.
These tend to be the most quality audiences at scale but you do require scale to make them work properly.
Speak to your audience
You wouldn’t sell steak to a vegetarian.
The same goes for copy and copy that goes over the creative, website copy, and any other copy and creative that you use to position your brand and products.
Your audience should always come first, who they are, what they value, what they care about, what matters to them (keep an eye on these questions, they will show back up later).
Design creative for your audience
Creative should match the audience that you’re targeting.
If you’re targeting hikers, use hiking photos and backgrounds, then use the city. If your product lives in the kitchen, show it in the kitchen.
Without fail ads relating to activities, we participate in grab the eye regardless of the actual product.
So, data collection starts with the inputs before the first bit of data is collected.
You, as the brand, are priming the understanding of which audience you’re targeting with which messaging.
- The journey for someone that comes in via an ad v. organically can be different as well
- Organic always lands on the homepage while the ad always lands on the landing page
- The stories are different, the experiences are different
Data Collection via Popups, Quizzes, Embeds
Where do you get data from? More specifically zero-party data.
The top places we look to collect data from customers are in the following order:
- Sign Ups
- Progressive Profiling via emails
- Surveys including post-purchase
We can put them in multiple places on the website during the browsing experience when it's most relevant to the customer’s journey.
The data itself is worth more than the discount provided.
This is the question that comes up right after someone signs up.
Rather than a thank you for signing up, a coupon code right away, or anything like that, how many people provide data past the email sign-up?
A great sign-up gets between 5-10% so with the above example for every 100 people signing up you’d see about 5 people signing up and providing 4 data points a person or around 20 data points.
With the high end being 10 people signing up and collecting 40 data points.
Sign-ups are an underutilized part of the customer journey. They have historically been one-sided where a company exchanges a coupon for basic contact information.
In terms of a data-driven strategy, the highest percentage of people you run across throughout your entire customer journey will come from email signups.
That’s what makes this the top place to collect data from customers.
It’s also the one place to stand out, not a lot of brands are currently using it. It’s always better to be one of the first when it comes to data collection.
In fact, data shows that more than 90% of people that sign up provide up to data points during signup when the questions relate to the customer journey and aren’t too personal of nature.
Number two on our list is quizzes, which are used as a way to help customers find the product that is right for them.
If done correctly they can be incredibly valuable and helpful. There is a split on where they can be used, depending on the brand experience they can be goldmines for collecting data relevant to a buying experience.
Providing product suggestions and recommendations is a great move when you have a large number of SKUs.
Stats vary but once someone takes a quiz they sign up at a rate between 15%-30% however the number of people that see a quiz is a lot lower than those that see pop-ups.
The hardest part about using quizzes is that they are very focused on the customer journey so by their very nature they tend to be about the experience, not the trade.
What we mean by this is that when a customer answers questions on a quiz they are more interested in the results and if a company gates the results in order to collect an email address the experience feels a little disingenuous.
Most brands put quizzes on specific products or collections that require the customer to quickly answer a few questions to get a recommendation.
We’ve seen a lot of good examples of quizzes, though the more appropriate term for them is likely wizards.
There is a hybrid that has been launched recently that puts a question before an email or phone collection, this is a way of getting a single data point before requesting a piece of personal information.
The micro opt-in has been labeled as a means of getting a commitment that makes people more willing to share their information.
The irony of this is that when brands ask for both an email and a phone number the most severe drop-off happens at the second step when requesting a phone number.
People are careful with their information, with the latest rollout of iOS 15 and the ability to hide emails, the future of quizzes where you need to provide an email to see your answers is done.
In fact, we have strong feelings that the old tricks of providing value before asking for information will likely be impacted as well.
These are ranked 3rd on the list because we see these as being triggered by buttons on a page. Rather than a quiz that is also triggered by a button, we see these as becoming part of a page.
It’s all about utility, more testing has to be done but we’re bullish on this becoming a long-term channel of data collection.
We think about things like sizing, return policies, estimated shipping fields, all of which can be used to collect data about the user during their customer journey.
These are still very new and not widely used.
Embeds with good strong CTAs can also find their way into Landing pages to make it easy for people to complete offers.
Progressive Profiling via Email
This tactic has become more mainstream where brands can ask a question via an email and based on the click in the email tie back a value directly to the customer's profile.
This points to a theme that hasn’t been touched on yet: in order to collect data a brand needs to have an identifier for a user, this is usually either an email address or a phone number.
This hits down on number 4 on our list in that it requires an action on the brand, they need to send an email and a two-step action on the customer, they need to open the email and click a link inside of the email.
Globally speaking in ecommerce the open rate on most emails non-segmented is around 20% whereas hyper segmented top out at around 60% of which anywhere between 2-10% of people will click through.
The range is large but from these, we already know that the max data points, remember only a single data point per email click, for 100 people comes out to about 6.
So the data conversion point drops down to 6% for a single point of data.
Should brands be using it? Yes, absolutely.
Surveys including post-purchase
Surveys are the age-old go-to for brands, usually, they come to subscribers and customers via email and request people to answer questions about their experience in exchange for a discount.
Successfully collecting data via survey depends on a few factors including the number of questions, the offer for filling out the survey (they take time), and the relevance of the survey to the customer.
Also of note, here are the types of questions the survey asks. Marketers love to slip in more long-form questions when sending out surveys, and these tend to reduce the number of answers that come back.
Delivery usually comes via email, which requires the two-step process from above but adds more questions to answer.
General response rates with great offers with top-performing delivery tend to average less than 7% of completion for answers.
Most surveys are reserved to customers that have purchased to get the most evident feedback as those customers have a vested interest in helping out the company to grow to assume they like the product.
This is a smaller percentage of the overall list, so effectiveness in comparison to a more significant part of the list can impact this percentage.
This brings us nicely to the post-purchase flow.
Massively popular these days is a post-purchase survey that can ask questions about where people found out about your store or product and any other questions about their experience.
These tend to have a high completion rate. As stated above, the intent is already made, the order in this case, which means that the customer feels that it’s more comfortable to provide information.
The downside of the post-purchase is that only 2% of customers on average purchase and of those only 30-50% complete the post-purchase survey. So it drops to about 1% of people that visit a website.
Data Collection Wrap Up
As a brand, you should use a combination of all of these methods to collect data about your subscribers and customers.
From a leveraged data strategy, you should seek to collect as much data as possible prior to the purchase.
This is your largest pool of data, it’s always best to collect as much data as possible to better understand the customer journey prior to purchase.
Decisions made to share data post-purchase don’t always map to the reasons that someone decided to make a purchase.
There was a lot of time spent on this section because it forms the basis of what comes next and creates a split.
Without data you can’t build the right half of our flow above, essentially as a brand, you're guessing.
Personalization via Retargeting Ads, Emails, and SMS
So people gave you data about themselves beyond just an email or phone number, it’s time to get personal.
Trends are your friend. From our diagram we can see instant impact on a few key portions of the customer journey, we’ll get to how to leverage this data back to your acquisition and prospecting too next.
Where we are currently…
- Retargeting because someone visited a website
- Retargeting someone because they signed up on the website
- Retargeting because someone looked at a product
- Retargeting because someone completed an action on the website
This is a valid strategy and is used on the left side of the flow chart above. It’s been used for years and been quite successful, until recently.
Tracking is quickly disappearing. iOS devices have largely opted out of tracking.
This has created a shift to put pressure on brands to collect more zero-party data and build out their own cohorts and targeting based on the direct intent data from customers.
So when we look at the right-hand side of the flow chart above, we have types of questions that we outline that cover what the customer is interested in, what matters most to them, how much of something they currently own, and when they are looking to purchase.
So what does this do for retargeting ads?
Option 1 from above was retargeting based on actions taken with products and leveraging the existing benefits of the product to the audience that visited.
This is pretty much a guess.
Option 2 is to take the information provided directly by the customer, group them with other similar customers, create a segment and export that to Facebook as an audience and retarget directly to them based on the actual things they told you that mattered to them during their sign up and buyer journey.
The second option allows you to speak directly to the customer using the information they provided.
Most emails aren’t personalized.
We’re not talking about sending an email using the first name in it, we’re talking about the biggest problem with email.
When you unsubscribe from an email the first thing a brand asks you is, “Why are you unsubscribing?” but none of them ask you during sign up why you are subscribing or even what you’re interested in.
When we shift to a data-first approach we look to collect information so we can personalize the type of content that we send out from the first email.
There are things that we want to hear about from brands, there are a lot of things we don’t want to hear about from brands. Not only that, we don’t as consumers need to hear from companies multiple times a week with different offers, sales, offers, etc.
There’s a huge difference between getting emails that feature content, explanations, social proof relating to the reasons that you’re looking to buy from a brand v. just getting generic emails that are built to sell all at every touchpoint.
SMS has grown massively in the last year and will continue to grow as iOS 15 and tracking start taking away from other channels like email. The current process of asking for a phone number then sending a limited amount of SMS messages a month.
Like email though this channel, if not personalized, will just get ignored.
When you go more personal via the communication channel, your messaging should follow.
SMS is a two-way communication and should be used that way. If you’re using it for marketing, you should use it to provide enjoyment or value.
Those of your customers that choose to share their email with you are exactly the kind of people you should ask for more data from.
There’s a big difference between sending SMS that is generic about offers v. sending personalized offers based not only based on the data shared with you directly as a brand but activities took on the website as well.
Personalization via Ad and Email Campaigns
- Can you personalize the welcome flow?
- Does the abandoned cart flow?
- The browse abandonment flow?
How about the email campaigns that you send out to customers? All of the above can’t be done without data.
iOS 15 just took away open rates, something that Brave Browser did a few years back, tracking in browsers? Yeah, Google Chrome is the only one left that hasn’t turned it off by default. (insert obvious reason here)
So how do we leverage data through personalization?
The majority of sales come from the welcome series and the abandon cart emails, depending on how large of an abandon cart rate you have.
Where people get this part wrong.
When someone signs up for your newsletter they get the welcome series, most people are bumped out of the welcome series after they make a purchase. This is a standard operating procedure, so this means that the only reason for the welcome series is to sell a product?
Basically. That’s the only reason we as marketers have decided is the reason people sign up to receive emails from us. That sweet sweet coupon code and the unyielding desire to want to part with our hard-earned cash for another consumer good.
But what if we signed up because we liked the brand and the lifestyle it was part of?
My favorite example of this is that people that participate in activities tend to be more loyal to specific brands. Snowboarder? You probably know most of the brands in the industry. You probably remember older brands as well like Forum who have long since been sunsetted.
What if the emails that you sent brought people into a community around creating products for a community?
This is the difference in using data, people will get email flows based on behavior automatically, which are all conversion-related.
But the welcome series? Personalize it to give an introduction to the brand, assume that this is your opportunity to sell people on the lifestyle of your brand and the enjoyment of receiving your emails rather than just seeing something that is trying to make a sale.
Leverage data collected to build that narrative.
Everyone knows what you make, they signed up for the email, instead tell them what they may have missed.
If you’re sending out emails for abandoned carts there are two different flows, one for those that have purchased and one for those that haven’t purchased previously.
Even knowing this data most of the time you don’t know why that person purchased it the first time.
But with data…
Jazz up those emails with social proof and reviews that are relevant to what matters most to the customer in the collections or products that they added to the cart. Position your messaging and content to speak directly to the customer.
There’s a big difference between, “You left this in your cart” and “We saved this sturdy masterpiece in your cart for you” where we know that what matters most to someone is the sturdiness of an item.
Post Purchase Emails
Never was there better a time to hype up expectations.
If you don’t know what matters most to someone or how many of something they own or how often they do something, there’s no way for you to articulate that post-purchase journey.
Else, you’re just using the same generic, “Hope you love your [insert product here]!”
Pro Tip: If you go plain text on these emails it feels way more personal.
If someone tells you what matters to them in the product, follow up to ensure that their experience lives up to their experience with the product.
If you don’t have this information, you can’t form a personal connection with the customer to follow through on an experience in a detailed manner.
For example, I tell you that I like beer and I really care about flavor. I buy beer from you.
You can say, “how was the beer for you?” or you can say, “what did you think of the flavors of the beer in your variety pack?”
You’re going to get more value from the second question, now you have a review that you can repurpose into your copy and your ads and leverage it out via email to everyone that specified that they too care about flavor in their beer.
Send stuff that matters.
You can guess about what matters to people, what kind of things they are interested in, or you can ask them and tailor campaigns that push messages and products to them that they have told you that they are interested in and hype up new features or existing features that meet them with what makes them great.
Content upgrades of paid ads
Every brand spends money on paid ads. A lot of people hype creative and the need to constantly be creating new creative.
When you have zero-party data from subscribers that describes the things that matter to them most in a product, their current buying cycle, and other data, use it.
Not only that, when you start to see patterns in the data that shows who is more likely to purchase, turn around and leverage those patterns in ads to level up your ad game so you’re appealing to more people likely to make purchases with you.
By now you should start to see the simple differences of taking a data-driven approach and how it plays into the customer journey.
The best part is that the flow continues to build on itself.
To recap why we collect zero party data during sign-ups:
- We can personalize emails and SMS
- We can find patterns in data to optimize our ad spend
- We can create personalized retargeting ads
- We can maximize website copy
- We can personalize post-purchase communications and reviews
- We can update website copy to match our most profitable customer journeys
- We can create better ads by leveraging data trends
- We can create lookalike audiences to find more people that showed intent
- We don’t have to rely just on guessing entirely