March 4, 2024
Post-holiday is a perfect time to do some forensic research.
With a ton of shopper data to evaluate from the holiday shopping season, it is possible to make some important breakthroughs. This research is the key to creating a “customer movement” strategy, which turns visitors into buyers, first-time buyers into repeat buyers and activates loyal shoppers more often.
I think of this process like a plumbing plan: there are a series of buckets and pipes into which every visitor and customer falls.
First, visitors come in through the spicket and based on what they do, they go through a pipe into a bucket. Perhaps they bought a discount item, or carted a high-value item.
These signals then are used to drive outreach to move them through the pipe to the next step.
What this process does best is remind retailers to keep moving, keep evaluating and keep interacting with customers in a way that is directly related to these valuable shopper signals.
Not every shopper's behavior matters equally when it comes to evaluating who the high-value and low-value customers will be over time.
Some signals indicate higher value, i.e. those who buy more products, buy higher-priced items, deliver a higher margin, and ultimately become high-value, long-term customers.
The first step is to identify those key buyer signals that tend to be tied to high value:
Where they came from. Knowing where a shopper was before they got to the site matters so that retailers know two things: first, where to spend their time and money attracting the higher value shoppers and, second, how to market to shoppers on the website depending on from where they came.
Someone who came from an affiliate site that tends to attract bargain hunters might not be as valuable as someone who came from a blog that reviews products and probably should not be given the same treatment.
Using an attribution model, retailers can start to better connect the dots from the originating URL to know what channels and types of paid media are driving the most valuable shoppers.
Channel preference. A retailer with stores and a digital presence should be aware of a visitor’s entire channel activity. They might live near a store and use the website to order items that were out of stock in-store.
Not only is this kind of information useful for personalization, it can also contribute to their overall value.
Multichannel buyers tend to be higher value than single channel buyers and could be worth pursuing with well-calibrated offers.
When they buy. Sure, someone who buys at midnight might be less valuable than someone who buys at lunch, but I am talking about leading indicators such as the period of time for a customer buying between a first and a second purchase. This metric is often predictive as to the future of the customer’s buying cadence.
If there is a long gap, longer than average, they are likely less valuable over time than someone who buys frequently.
Similarly, retailers want to also understand the time of first visit to the website to the transaction using tools such as an identification platform. I used Bluecore with great results in the past.
This key statistic could be predictive of long-term value as well. If they came today and bought right away, they might turn out to be better than someone who visited 30 days before they finally bought something.
What they buy, and for how much. Any returning customer has a history that can provide great insights about what they might do next.
If they bought a full-price item, a retailer might not need to waste a promotion offer on them as they are likely to buy full price again.
Similarly, if someone tends to buy clearance, it is better to steer them towards what is new on sale than share a discount for a full priced offer if that is not as beneficial to the bottom line.
How much they cost. When creating an acquisition strategy, retailers often look to their highest lifetime value (LTV) customers as a model for who to target with top-of-funnel campaigns.
However, these customers might be very expensive to acquire. There might be other customer segments that have a slightly lower LTV but are much easier to acquire, yielding a higher net return for the retailer.
What is more, many retailers overlook the signals of current customers who might be willing to move to a more valuable customer bucket if given the right opportunity such as an invitation to be a VIP or an email that showcases products in adjacent categories of which they were not aware.
How much revenue they generate. This metric might be the most frequently misunderstood when calculating LTV.
Topline total revenue is only part of the picture.
For example, customers who buy a lot of products that they return, or that they buy on discount, may make the company a higher total dollar amount than a less frequent buyer who only buys full price and never returns anything, but the net revenue for the second customer could be a lot higher.
It is important to consider the revenue and the cost of each transaction including customer service, discounts, returns and loyalty rewards.
The second step is to marry these insights with product profiles.
Smart retailers know that customer signals are only half the story. It is also important to consider the characteristics of the products themselves.
Someone who buys items that have a high margin is more valuable than consumers who buy items with a thin one.
Similarly, someone who has purchased an easy-to-fit item such as a T-shirt is likely not going to return the item compared to someone who purchased a fitted dress.
These product features married with product information set the stage for much more effective marketing.
KNOWING THE REAL value of a customer, and what is actually contributing to that value, helps with everything from where to invest at the top of the funnel, to what offers to share with different customers, to how frequently to reach out.
With these insights in place, the plumbing plan can help retailers focus on the signals that matter to drive dramatically more value per customer, no matter in what stage they are.
Mark Friedman is president of Details Interactive, Westfield, New Jersey. Reach him at mbfriedman61@gmail.com.
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