An infamous old truth stated by retailer John Wanamaker is, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”

Today, that statement is a fallacy.

With the data and analytical power retailers have at their disposal today, companies can measure the cause and effect of advertising and communication down to an N of 1. The cause and effect of marketing messages can be measured. Plus, if customers opt in, marketers can know consumer actions each time they engage with a brand.

Leveraging the power of data, brands can maximize their marketing effectiveness by focusing on six customer ratios. Enumerated below is each ratio, its calculation, and why it gives insight into increasing a company’s average customer lifetime value.

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1. Discount ratio

Calculation: total discounts/total orders

Insight: Calculate a customer’s discounted purchases divided by total purchases; the closer this figure gets to 1, the more the customer’s buying decisions are based on a discount and the lower the marketer’s margins.

Such customers will quickly eschew you for a lower-priced competitor. Retaining these bargain hunters is like chasing a rabbit. These consumers’ next move is always to follow the deeper discount. It will leave a brand and competitors in a race to the bottom — the bottom of margins and profits.

2. Churn factor

Calculation: time since last activity/activity frequency

Insight: An individual customer’s churn factor is measured by dividing the time since the customer’s last activity by the customer’s activity frequency.

It is essential to recognize that every customer is different – each buys at their frequency. Some customers make several purchases yearly, while others tend to buy around holidays – not just the November-December holidays, but also Mother’s Day, Father’s Day, etc.

So, every customer has a unique churn factor. Using a simple, time-based metric with no regard for each customer’s particular activity frequency is a mistake.

For example, we have seen some marketers apply a blanket rule to reach out to customers after three months of inactivity and categorize those customers as churned. This one-size-fits-all approach ignores the customer’s interaction frequency and usually leads to poorly timed and ineffective marketing actions.

It is also sloppy, lazy math in this era of data analytics. It leaves the marketers guessing about each customer, like John Wanamaker.

Marketers must be alerted to each regular customer who starts buying less often or in lower quantities. If a regular customer starts buying less, it is a sign that something is amiss or that the relationship has derailed.

The higher the churn factor, the more likely the customer has already churned, never to return.

Each customer’s churn factor should be amalgamated into a company-wide churn rate formula: (Lost Customers ÷ Total Customers at the Start of the Time Period) x 100.

Improving the overall churn rate is achieved one customer at a time.

3. Item ratio

Calculation: total items purchased/number of purchases

Insight: The items ratio calculates purchase volume to measure if the customer buys only a few items at a time or if they buy in volume. In addition, based on specific SKUs purchased, a brand can be informed on how the consumer uses the retailer.

If a customer has a history of bulk purchasing and there is a sudden volume drop, it could indicate that the customer had a household change, such as a child going off to college. Conversely, an increase in volume could mean an addition to a home or business.

Also, if the customer spot buys select items (e.g., auto parts), it can signal a marketer to concentrate messaging to the customer only on auto parts and related items. If, on the other hand, the customer buys auto parts, household, and other items, then it is a signal that the customer is open to filling a broader set of needs.

4. Returns ratio

Calculation: total items returned/total items purchased

It may seem counterintuitive, but customers who return 20%-50% of their purchases are often of higher value to the brand than those who have not returned any purchases (or returned everything they bought).

Why?

There is a rationale behind this peculiar customer behavior. Returns are a staple of online shopping. It is part and parcel of the digital shopping experience, and many savvy online shoppers embrace it as part of the buying process. Looking for a bathing suit? Not sure about the design – try more than one and keep your favorite. Not sure about the size? Do the same. Some leading brands, such as StitchFix, have actually baked this dynamic into their sales methodology.

Further, a return is an opportunity for a second interaction with the customer. Some brands even have a Chief Returns Officer to optimize the interaction.

Great brands learn through data that the customer who returns is the customer with a give-and-take relationship with the customer. They are there for the customer in the long run, not just the immediate sale.

5. Retail ratio

Calculation: total purchase in store/total purchases

Insight: Marketers should examine a customer’s purchase history based on the place of purchase. All online? All in-store (increasingly uncommon)? A hybrid mix includes customers who buy online and at physical stores and those who order online but sometimes or always pick up at the store.

Customers falling into the hybrid model are omnichannel customers and should be marketed to as such.

Omnichannel marketing solves this dilemma. Consumers interact with a brand as one entity. Conversely, many brands communicate with consumers via siloed channels. For those silo-channeled brands, no team, whether email, chat, in-store, or web, has one single view of the customer.

Effective Omnichannel starts with customer communication with the brand. In doing so, marketers can marry all available customer data to one source of truth. It houses retail store data with online data and more to optimize all customer experiences in one channel.

Our experience is that some retailers empowering reps with Omnichannel information have achieved a 53% increase in monthly average net revenue and a 15% decrease in customer churn.

6. Ecommerce ratio

Calculation: total purchases online/total purchases

Insight: This is conversely related to the retail ratio (#5 above). Marketers need to know if a customer makes all purchases online. If so, the marketing effort should be online as well. However, if the e-commerce ratio starts to decline, the customer has shifted from an online-only customer to a hybrid (omnichannel) customer. However, this is less common and happens if a firm opens a physical location close to the customer or has consistent e-commerce purchase and fulfillment issues. If the former, marketing efforts should shift appropriately. If the latter, seek to fix any e-commerce issues.

Conclusion

Six ratios can give marketers a sixth sense of each customer. Above all, the ratios enable a more effective marketing effort, with a better return customer lifetime value. And, unlike Wanamaker – the marketer will know the effectiveness of each marketing interaction.

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