Three more data-driven marketing decisions you can make today
Data-driven marketers routinely rely on transaction data and customer analytics to drive their programs. More traditional marketers hear their claims, perhaps even see the results, but don’t know what to do or where to start making data-driven decisions for themselves.
Our blog post, Data-driven decisions you can make today, explained why marketers should use the data-driven approach and offered methodology for two such decisions. Here are three more decisions that are better and smarter when there is a data foundation driving your marketing choices.
Which customers are most worth keeping
Why make this decision: Situations for which you want to know your most valuable customers include:
- Reactivation campaigns, where you may need to concentrate your resources on the customers most worth retaining
- Rewards programs, where you want to know which customers to thank and which to get lower level incentives
- Direct marketing campaigns with expensive collateral such as an individualized marketing mini-catalog
How this decision is usually made: Most often, companies use total revenue received from a customer to measure their value. Occasionally companies pick RFM score as the value metric, or consider every customer in their active file to be valuable. A few companies calculate Customer Lifetime Value (CLTV) but usually do so on a segment basis, not separately for each individual customer.
How to make a data-driven decision today: Your company should develop and use a value metric. A good value metric will correlate purchases in the next quarter, with total amount purchased, with number of items purchased, and inversely, with recency. While revenue will be one component, it is not the only component. At Loyalty Builders, a principal component analysis usually shows revenue often contributing less than 40% to the Loyalty Score metric we use to measure value.
Which customers to call when you absolutely need a sale
Why make this decision: While a balanced approached to customer communication is best in the long run, there are times when you may need to make a more aggressive approach to some customers to satisfy short term revenue goals. Then knowing which customers to call and expect a positive response can be important.
How this decision is usually made: Salespeople almost always go after the customers who spend the most. They are certainly good prospects for another sale, but there are other metrics that can identify a likely near term buyer.
How to make a data-driven decision: This is essentially a customer-centric decision, but you can approach it from product-centric data—look for customers with high up-sell probabilities. That is, look for customers who have a high likelihood to make another purchase of some previously purchased specific products, and pitch those products to those customers. We routinely deliver these up-sell probabilities, so it’s easy to find the customer targets.
A second method is to use your Likely Buyer scoring. Whether you rely on traditional metrics such as recency and RFM or use the newer Likely Buyer Score from Loyalty Builders, this type of metric identifies customers ready to buy something in the near future.
A third approach is to look at customer buying patterns. Our Purchase Delay metric, for example, measures how many purchases a customer has missed, based on their buying patterns (and each customer has their unique pattern). A Purchase Delay of 2 means that a customer has missed two purchases off their usual cycle and is obviously not a good target if you need a near term sale. Customers with Purchase Delays less than 1 are actually accelerating their buying rate and could be excellent prospects for that sale you need.
When to campaign to a customer
Why make this decision: Not every customer is ready to buy every time you are ready to send out a communication. If the communication cost is low (for example, an email) and you bombard everyone, you risk being turned off as spam. If the communication cost is higher (for example, a postcard), you risk wasting a lot of money sending mail to unresponsive customers. Of course you need to maintain some contact, some touch, but how much and when are questions that don’t have just one answer.
How this decision is usually made: Almost all companies make this a calendar-based decision. For email, most companies mail everyone in their active file from once a week to every day. Postcards are sent out monthly, and catalogs are either sent seasonally or monthly.
How to make a data-driven decision: Calculate a likely buyer score, the probability that a customer will make a purchase in some pre-determined time period covered by your communication, typically one month. Then send your more costly pieces only to those customers whose likely buyer score is greater than 1% or 2%. A solution like Longbow calculates a Likely Buyer Score for every customer every month, so it’s really easy to identify these customers.
It’s your call
It may be easier for you to make some of these decisions instinctively, rather than doing the work to make a data-driven decision. Sometimes relying on your gut is the way to go but even if you do take that path, look at what the data says, too. If your instincts and the data agree, you’ll be strengthening your instincts. If they don’t, at least you know the alternatives.
It’s your business. It’s your call. Give your data the chance to help.