How to optimize the customer lifetime value
Customer lifetime value is probably one of the most important metrics that you can measure as an eCommerce business, and sometimes arguably even more important than popular metrics like revenue.
This is because, very often, you will acquire your customers at a loss, only to recover their acquisition cost through repeated purchases that happen days, months, or even years after the initial purchase has occurred.
For example, a person called Jackie saw your product advertisement on Facebook, an "Anti-wrinkle experience trial." She became interested, visited your website, and ended up making a purchase of that trial product for $30.
However, the problem is that your overall cost per acquisition that day was $100, much higher than the initial value of Jackie's purchase, so Jackie's acquisition came at a loss - if she doesn't come back and buy again, that is.
After seven days, Jackie felt that the product was good, returned to your store, and bought a formal dress. That entire transaction cost her $130.
This entire second transaction did not cost you a penny on advertising, making you profit a total of (130+30-100) = $60 off Jackie.
A month later, when your product was promoted through email. Jackie came to your store again and bought a suit without hesitation. She spent $300, making her total profit to your store $360.
Through the above cases, we can learn that a user In the entire lifetime, the longer lifetime, the greater value, and the higher purchase frequency, the greater the value of the user.
Since user value is so important, let’s break it down in detail in this article and figure out together how we can optimize it throughout our customer journey.
In this article, we are going to analyze the lifetime value of users in two stages：
The acquisition stage
Loyalty stage
The first purchase stage covers the acquisition of your customer, whereas the loyalty stage describes things you can do to get them to come back and buy again.
While initially planned as one article that covers both of the stages, we quickly realized that there are so many topics to cover under each of the phases that it is best to release and edit this post in separate sections.
This article is going to cover the first stage of our journey to increase customer lifetime value, getting our customers to make a purchase in the first place.
Then we will move onto measuring your effectiveness in elongating your relationship with your customers through post-purchase metrics.
Finally, we are going to wrap this three-part series up with some discussions on how you can apply everything talked about in this series into your day-to-day activities, given severe resource restraints on your company.
This article is aimed to be both comprehensive and practical, so if there are any points that are not clear, or you would like to learn more about.
Let us know in the comment section or join our analytics Facebook group to learn more about these topics with like-minded people and we will work on creating an article to satisfy your needs.
The acquisition phase
We begin our analysis with the acquisition phase, which begins with brand recognition and ends with the first purchase (or conversion) of a customer.
In this stage, typical user actions include but are not limited to:
Seeing your ads on a social media or organic platform
Interacting with your ads above,
Visiting your home page and other crucial pages of your website
Adding your product to cart and begin the checkout process
Making a purchase
For the sake of simplicity, we are further dividing the acquisition phase into three sub-phases: 1) Cognition 2) Engagement and 3) Conversion
Cognition
Let’s begin with cognition.
The ultimate goal of cognition is to make your customers remember and recognize your brand as a valid product/service that can serve their needs.
To achieve this, you need to cover two key factors:
find the people that actually need your product, and
2) convince them that you can fulfill their needs.
We usually don't have enough power to cannot control the needs of our customers - they arise from their life experiences and are typically unique to their demographic.
Therefore, the key here is to find the correct people that have the needs in the first place, rather than trying to generate needs in an audience that is less attentive.
On the other hand, convincing them that we can fulfill their needs is a factor that is well within our control, and we can do many things to make our messages more convincing, such as:
Attractive and authoritative graphics,
Using social proof to establish authority,
Discounts or limited offers to increase the scarcity of the product.
In summary, the best way to maximize your cognitive effectiveness is to find an audience that already has the need, and offer them a convincing message that they cannot say no to.
In eCommerce, this looks more like this
With the conceptual framework established, let’s talk about analytics.
Regardless of your acquisition channel (Organic vs Paid), method (Video vs Static), two important categories of metrics will come up repeatedly to help you understand the effectiveness of efforts:
Impression
Engagement
Impression: Impressions are the total number of times your audiences have seen your content.
Variations of impressions include reach (basically unique impressions) and impressions.
Reach is the unique number of people who have received your message on a specific platform, and sometimes maybe better than impression if your messages are being over delivered to your audiences - this situation is rare for most companies, however.
Please note that the audience here may NOT be your target audience, they could be any audiences that you have configured on your advertising platform or any person who has searched for the search term that you are optimizing for.
The impression is very important because it can give you an indicator of where your messages are being displayed, which creates a foundation for the next two metrics.
Engagement: engagement metrics are any action someone takes on your Page or one of your posts.
The most common examples are likes, comments, video views, shares but it can also include checking in to your location or tagging you in a post.
Engagement is a crucial step to the success of your word of mouth because it can help extend the organic reach of your messages.
Likes and shares expose your posts to your audience’s extended network and make the Facebook algorithm more likely to float your post up organically to a more targeted audience.
Just to put into perspective, each like or share can extend the reach of our messages to up to six or seven new people.
That’s a lot of extra exposure at no extra cost.
Engagement is important to marketers because engaged users form the basis of a healthy business.
It is what helps advertising break through the clutter to ultimately motivate consumers to research products and take action.
In Summary: All metrics of the advertising platform described above, such as impression, reach, and engagement, show how well whichever audiences you are targeting are receiving and spreading your message.
By optimizing the above metrics, your brand will be displayed to more appropriate people, so that more potential users can visit your website participate in your web page and smoothly enter the next stage of their customer journey user process.
This optimization may happen on a manual basis by your marketing team, but it also may happen through the optimization algorithm of platforms such as Facebook and Google (through SEO, for example) - do not ignore the latter.
After attracting your customers on a rented platform such as Google or Facebook, we now move onto the second stage of our customer journey - engagement
2. Engagement
The engagement step starts when your customer has successfully entered your site through advertising.
Although they have cognition for your brand, they seek a deeper understanding of your brand and product before making a decision to make a purchase.
During the engagement, they may perform actions like:
Browsing your website to learn more about your products,
Signing up for your newsletter to receive more information and deals about your brand
Adding the product that they are interested to cart.
Even though the behavior of your users may vary, their goals of all of those behaviors are aligned - they want a great experience or they will just leave.
For example, a user may come to your website to browse your product information.
However, when she/he logs in to the homepage of your website, the homepage is loading very slowly, resulting in the user leaving immediately due to bad experiences (this is a bounce).
Therefore, to fully engage your users and make them ultimately purchase, you have to optimize your website experience.
For the sake of simplicity, we are going to divide up your user experience into three categories - 1) Landing page visit 2) Other key page visits 3) Add to cart / Lead form submission
Landing page visit:
A large portion (above 40%) of your users will visit your home page, and leave without continuing their experiences.
In many cases, this is okay because they might not be a great audience to make a purchase in the first place, or they simply have obtained enough information from your website to make their decisions later.
However, with that said, you still want to push as many people on your website beyond the first page as possible - and you measure the effectiveness of your efforts doing so through a metric called the bounce rate.
The bounce rate is one of the most important metrics of Google Analytics.
Many people that I have talked to ask me if there is a benchmark on bounce rate - unfortunately, there is not - and bounce rate of different companies, website layouts, industries differs drastically.
However, if your bounce rate is over 90%, something is wrong with your tracking setup, and you should have it examined here.
Other key page visits:
Beyond their initial visit, users will also visit other key pages on your website such as your product page, about page, before making a decision to add your products to their cart.
With the customer journey accelerating in the past 5 years, it is very likely that they will only visit a few pages of your website before making a final decision to proceed, making those websites absolutely crucial for your business.
Metrics you can track in this stage can be divided into two categories:
those that describe the quality of the visit
those that focus on visits on key pages.
Let’s begin with the metrics that describe the quality of the visits,
Which are session duration and pages per session.
The metric of session duration tells you how long people are spending on your website.
This data will help you see trends and patterns in what content performs best and what your audience is most interested in.
An alternative metric that describes similar information is pages/session, which shows how many pages are visited in a given session.
However, this metric is gradually falling out of favor due to technologies such as localized routing (no new page views on content change).
The second category of metrics is the one that focuses on visits to the key pages such as the product and category page.
For those pages, you want to look at the exit rate, bounce rate (if applies), time on page, and other relevant metrics on a page-by-page basis.
Add to Cart
The add to cart behavior is often misunderstood in eCommerce analysis.
When a user adds your product to the cart, it means that they have the intention of making a purchase, but it does NOT mean that they are ready to make a purchase at this very moment.
For this reason, the average cart abandon rate for an eCommerce store is very high (up to 70-80%), and it is completely normal simply due to customer behavior.
This means two things:
Add to cart is in fact an engagement metric, rather than a conversion metric, and your journey is not finished yet.
Add to cart is a very good measure for how good your website attracts customers and convenience to buy.
You really need to implement cart abandonment strategies to continuously push your customers through the funnel.
For the purpose of this section, we are going to measure our add-to-cart effectiveness with the Add to cart rate metric.
This represents the percentage of your traffic that has added a product to their cart.
What I have said about the bounce rate also applies to add to cart rate - it is very different depending on the type of product you are selling and how many competitors are out there.
With that said, a site with add-to-cart rates below five percent may have problems with:
site navigation
site search
product selection
product presentation
or pricing, debug your site to make sure everything is working!
To sum up, in this step of our customer journey, we should not only pay attention to the experience of the landing page, but also additional indicators further down the customer journey, such as product page views, and add to cart.
2.5 Side note about customer journey dependency
“Before moving onto the next part of the customer journey, it is important to note that all of your metrics at the current step (engagement), are highly dependent on the metric from the previous step (cognition).
This “journey interaction” comes in two ways - the “direct interference”, and the “hidden interference”.
We will talk about the “direct interference” here, and reserve the “hidden interference” for section 3.5 because it will make more sense when we have 3 customer journey steps to consider.
The “direct interference” can be defined as interferences from a previous customer journey higher up in the funnel that directly resulted in the unusual behavior of metrics that is lower down the funnel.
The impact of “direct interference” can be most commonly seen when you just started running ads on your website - you will immediately see your bounce rate shooting up and conversion rate going down, simply due to the fact that paid traffic is in general of less quality than organic traffic.
The best way to avoid the impact of “direct interference” is to isolate your traffic from different channels and analyze them separately.
For example, you might want to analyze the on-site behavior of your customers of all paid channels, all organic channels as separate entities, and create different objectives on how you want to engage those two audiences.
The unfortunate fact of this approach is that the separation will never be purely clear, as much traffic from advertising sources may be recognized as “direct” or “organic” in a perspective of multiple sessions by the users - but it will remove enough interference for analytics to be valid.”
3. Conversion
Let’s move on to the third step: Conversion.
Conversion is like the last stretch at the end of a very long race - everything that you have done so far to acquire and engage with your customer has come to this point.
The concept of a “funnel” truly applies to conversion - once a user starts their buying process, is it very clear that they want to make the purchase, and is just going through the steps to finish it.
However, as they are going through the experience, any adverse experiences may result in them dropping out of the funnel and you have to bring them back to this point again.
Personally, I can think of multiple instances where I stopped the checkout process of a product only because I don’t have my credit card at hand and ended up not making the purchase at all because of it (that’s why PayPal and amazon pay are around).
So as an eCommerce owner, you must perfect your checkout process and make it as seamless as possible.
To improve, you must first know what’s wrong, and that’s where analytics comes in.
There are multiple metrics you should measure within your checkout funnel, but they generally all start with “enter checkout” and end with “purchase‘, or similar metrics that illustrate conversion.
Within the two critical points illustrated above, additional milestones can be created as metrics such as:
Enter payment information
Pick shipping and enter a shipping address
Create an account
Select additional add-ons.
The key to analytics here is that you want to organize data progressively by users’ checkout experiences, and identify great discrepancy, or drop-off points.
For example, if 100 users entered checkout, 90 created accounts, 70 entered shipping information, and only 38 entered payment information.
You know something is preventing your users from paying for your product, and you should consider adding additional payment options that fit the needs of your users.
Overall, conversion funnel optimization is perhaps one of the most straightforward but also most crucial points of analytics of your customer purchase journey, making it a great place to start your analytics journey.
3.5 More on interactions between customer journey dependency
“The model we have presented so far in this article, along with almost all similar models you have read on the internet have been simplified representations of your customers journeys to purchase.
However, the reality is that, in practice, the metrics introduced above do not behave the same as you intend them to be, nor are they as straightforward as they seem.
We have covered one major factor, knowing the “direct interference”, which can be bypassed to a degree by analyzing performance by channel.
However, the “hidden interference” is much more complex an issue to address.
“Hidden interference” describes the situation in which your performance later in the customer journey is impacted by how you approach your actions in the earlier part of the funnel.
For example, at the surface, you might see an audience from your Facebook advertising (let’s call this audience 001) performing relatively poorly over a week span of time, with a total of 5% add to cart rate and 1% conversion rate.
However, unbeknownst to you, this audience’s add to cart rate was 20% on Sundays, with a 5% conversion rate, but 2% add to cart rate and .5% conversion rate on any other days.
We call this “interference” hidden because it is impacted by a factor (or dimension) that is not known, and difficult to detect for a human analyst unless he/she is specifically looking for time’s impact on conversions at different parts of the funnel.
The example above, while seems complex, is actually merely a glimpse of the complexity of exploring “unknown unknowns” along your customer journey.
At the moment, I cannot say that we have a great solution to this challenge yet, but we at Humanlytics are working on approaches to uncover those hidden insights as we speak.
Conclusion
With the entire “initial purchase” journey described and complexities explained, we have come to a natural breaking point of this series.
Next part, we are going to cover how to measure and assess your customer journey beyond the initial purchase of your customers, along with tips on conducting those analyses effectively at your organization.
As usual, comment below if you have any questions or concerns about this article, love to answer questions or just talk!
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See you next time!