Find the best Analytics Software and Advisors to turn your website data into actionable, visual insights.
Welcome Guest | Sign In

Determining an Online Customer's Value

By Kshira Sagaar & Prashanth Baptist CRM Buyer ECT News Network
Mar 25, 2014 12:56 PM PT

Chris remembered his mom fumbling for her keys as she stepped out of the house, quickly locking the door and dashing toward the car. They were off to shop. Chris felt this to be a very clichéd way of shopping and always dreamt of an easier way to shop with less hassle.

Determining an Online Customer's Value

Jane, experiencing a very similar drill, never hated it once.

Over decades, the experience of shopping has taken many forms and now has crawled its way onto the Web, making life very comfortable for Chris. He does most of his shopping without having to move an inch. Although Chris makes some of his most important purchases -- like electronic goods, phones, luxury clothing, etc. -- on the Web, he buys his quotidian stuff at the brick-and-mortar mall.

What about Jane? Has technology made her life easier? Well, she doesn't quite ignore the online space; she mostly does her gazing online, though. She does order a lot of small trinkets from online stores, but she prefers the head rush of shopping in a physical store, like she did as a kid.

Now, is Jane a more valuable customer or is Chris? How can you identify which customer is more valuable and whom to concentrate on?

What we have here are two customers experiencing online shopping in very extreme ways. Between their extreme online shopping behaviors exists a customer gradient. This customer gradient includes a multitude of customers, each exhibiting a very different behavior from the other.

This natural customer gradient has forced online businesses to understand customers to their minutest detail and render them an almost flawless online shopping experience. Understanding and quantifying each customer prompts the question, "How valuable are my customers to the business?" To answer this question, one needs to know, "How has the customer spent his time shopping on my site?"

A customer's lifecycle can be classified broadly into the following three stages: Entry, Engagement and Exit, or the three E's. Businesses today use the three E's to seamlessly replicate a control system, capturing a lot of basic metrics, and where necessary, to incorporate enhanced strategies into a feedback loop to keep the customer from falling out of the system.

Running through a couple of important metrics -- each creating a new dimension across the spectrum -- will help quantify the associated dollar value of a customer.

Customer's Entry/Acquisition

Online retail businesses spend a lot on marketing themselves to acquire more customers. Pockets are only getting deeper, with an increasing movement of customers from in-store to online shopping, along with increased competition. Hence, there definitely is a need to understand the mode of entry of each customer to rank the profitability of the spending efforts.

Some of the common channels that businesses explore to pull new folks into the system are through Referrals, Paid Search, Promotional offers, platform-dependent apps for mobile devices, gift cards, BD with trusted partners and so on. Despite such well-defined acquisition baits, there are a lot of customers coming in through free and vaguely defined marketing mediums.

At this juncture, mode of entry serves as the first dimension to be analyzed, although you might be prejudiced as to which entry mode works best for you. But hold on -- mode of entry coupled with additional dimensions across the lifecycle defines the actual value of the customer.

Turning to Chris and Jane to build a story, let us assume that Chris got in through a paid search floated by a leading online retailer and Jane just stumbled upon, probably through a referral invite. Chris is one among a number of customers acquired after having spent millions on ad campaigns.

On the other hand, Jane was acquired virtually at no cost. Typically for any online business, Chris is supposed to be more valuable and is expected to engage and purchase more. But, is Jane any less valuable? Will she spend as much as Chris?

Customer Engagement

Customer engagement is the information pot of gold. Numerous dimensions can be laid out impeccably to pinpoint a customer's behavior. To analyze engagement, there are three basic dimensions to be explored: mailer response, visitation pattern and purchase behavior.

Mailer Response. Now that you have acquired a customer, the focus shifts to encouraging shopping. Most online business use email reminders as their weapon to attract, some with a certain amount of personalization built into their systems to enhance their targeting specificity.

The email reminder is probably the most important marketing channel and the revenue contribution attributed to it is a fair proportion of the total dollar influx. Paying careful attention to this will improve your ability to capture the most actionable customer-related information.

Metrics like open rate, click rate, average subscription period, current subscription status, time since un-subscription, type of mailers registered for, average time lapse between sending and the customer opening the mail, any particular offers/brands that made a customer reach the site, and subject line preference for opening an email can help quantify the engagement level.

Taking stock of these metrics as a measure of mailer response helps evaluate the customer and how the business reciprocates. This serves as the second dimension.

Visitation Pattern. Visitation data is one huge playground on which a lot of analyses can be built. It helps business to engage customers for the major chunk of their lifecycle. It can be used for rolling out personalized emails, targeting promotional offers at the right time, showcasing the right assortments on a page, and so on.

For the purpose of calculating the value of a customer, certain metrics like number of sessions, average time between sessions, frequency of visits in a product category, frequency of visits to specific sale/offers, frequency of visits to specific brands, the spread of visits across the assortment, dominant visit time, interest shown in discount offers, average days visited in a month, and many more such meaningful derived metrics can be used to quantify the customers' value, which forms the basis of the third dimension.

Purchase Behavior. Mailer response and visitation patterns offer metrics to gauge the interest of a customer. The purchase behavior is ideally the most optimal reflection of how a customer is engaged. In most online businesses, the visit-to-purchase ratio is a very small fraction, and perhaps this is the sole reason that capturing the customer's purchase information is also very critical. This is the fourth dimension, and it probably is the most important factor in determining customer's worth.

Purchase behavior can be captured by quantifying metrics like time spent in the system to make the first purchase, average time lapse between purchases, average order value, volume or high-end buyer, units per basket, likelihood of supplementary/complementary purchases, number of discount offers availed, brands purchased, most preferred category, payment method preferred, loyalty programs signed for, number of returns, number of cancellations, and repurchases using credit points if any.

Do you have a better understanding of the individual customer now? Who might be more valuable? You can lay your perceptions to rest, if you can assess the risk of losing a customer.

Customer Exit/Churn

No business wants to lose customers, but for most online retail businesses, nearly half of their customers will buy just once. Some repeat purchasers might also churn over a period of time. A subset of the metrics described in the above stages can help quantify the churn.

There are several statistical techniques for using the customer information captured to predict the chance of a customer churning. It might be a good practice to assess the exit from time to time. It gives a fair idea of the degree to which you should worry about your customers. It helps you to chalk out a plan and do a monetary estimate to learn which set of customers you should spend the maximum on for retention, as well as to strategize retargeting efforts by asking which offers/promotions will pull customers away from the exit -- or propel newer customers to engage more, and so on.

Being able to gauge this behavior of the customer is supplementary in arriving at the customers' value. This can be seen in the above illustration as the Exit values. This is our fifth and final dimension.

Tying the above three aspects of customer engagement to Chris and Jane, consider the following graphic:

Chart of Lifecycle and Value of an Online Customer
Valuing Chris vs. Jane - The Five Dimensions
Reading the Diagram: The greater the size of Chris or Jane in one dimension, the higher the customer's value will be in that particular dimension.

How Should an Online Customer Be Valued?

Evaluating the online shopper is not a one-dimensional task. Customer value cannot be learned through the common "money spent in the system" approach. It is the nuances about the customer that help businesses enhance their understanding of the customer and tailor the overall shopping experience. The five dimensions together hold the key to building that framework.

Valuing one customer more than the other is one side of the story. This framework will also help businesses serve the following purposes:

  • Provide clarity on customer value at each stage of the customer life cycle;
  • Help understand and appreciate the sort of data and information that can be captured;
  • Identify measures that can be undertaken to keep a consistent check on the customer;
  • Provide an opportunity to enhance their experience and hence the overall "value"; and
  • Evaluate the overall value of your online business.

So, finally, is Chris more valuable to your business or is Jane? Well, let's leave that to your interpretation -- whether you want to spend a lot of time and effort on someone like Chris or someone like Jane is completely driven by how you define "value," and that definition will emerge from this framework of five dimensions.

Kshira Sagaar, manager at Mu Sigma, provides data analytics expertise to Fortune 500 clients within the technology, pharmaceutical and retail industries. Prashanth Baptist, an associate manager with Mu Sigma, has provided innovative solutions to multiple online retail clients.

Facebook Twitter LinkedIn Google+ RSS
How do you feel about accidents that occur when self-driving vehicles are being tested?
Self-driving vehicles should be banned -- one death is one too many.
Autonomous vehicles could save thousands of lives -- the tests should continue.
Companies with bad safety records should have to stop testing.
Accidents happen -- we should investigate and learn from them.
The tests are pointless -- most people will never trust software and sensors.
Most injuries and fatalities in self-driving auto tests are due to human error.