How to Effectively Use Databases in Data Driven Marketing - dummies

How to Effectively Use Databases in Data Driven Marketing

By David Semmelroth

Data driven marketing campaigns are rarely done in a vacuum. Your company has data driven marketing campaigns on TV and radio and in magazines and various other places. Each of these campaigns has an audience, offer, message, and in-market date. These campaigns all have slightly different purposes and may reach different audiences.

Your database marketing campaigns need to be coordinated with your company’s wider marketing efforts. Your brand is most effective if it’s represented consistently. You don’t want your database marketing offer to be undercut by an offer being advertised on TV. Ideally, your company’s overall marketing strategy should be reinforced across your entire media presence.

That said, there are some things that database marketing is particularly good at. You have insight into what individual customers are doing. This insight gives you a powerful tactical advantage over broader advertising campaigns.

How to use data driven marketing to retain customers

You can lose customers in a number of different ways. They move out of your company’s footprint. They have a bad experience and walk out in a huff. A product wears out, and they replace it with your competitor’s product. They make a reservation and then cancel it.

In many cases, your database signals that a customer is about to leave. The customer may have logged a complaint. You know when the customer bought a particular product and when the product needs to be replaced. This advanced knowledge gives you the opportunity to intervene before the fact. You can contact the customer to address the complaint. You can communicate about the latest replacement.

How to use data driven marketing in cross-selling

If you’ve ever bought anything online, you’re familiar with the “People who bought that also bought this” pitch. This is a classic example of cross-selling. The basic idea is that there are natural product bundles: pen and paper, beer and peanuts, airline tickets and hotel reservations.

By analyzing your past purchase data, you can identify naturally occurring product bundles. This is a particularly powerful technique in consumer goods industries. Even a specialty retail store, such as a pet store, has a wide array of products.

Knowing that someone bought a dog collar or a litter box or a ferret cage is powerful information that can predict what they’re likely to buy in the future. Once you understand your product bundles, you can put that knowledge to work by monitoring future purchases. When a customer purchases a product that’s part of a bundle, you offer them other products in that bundle.

Product bundles aren’t unique to consumer goods industries. People often open bank accounts in bundles — an overdraft protection line of credit with a checking account, for example. Insurance companies often bundle auto and homeowners policies together.

Any industry that offers an array of products can benefit from understanding their product bundles. Cross-selling to customers who buy into these bundles is an effective way to increase sales. And it all starts with your database.

Upsell current customers with data driven marketing

Many companies have similar products that are differentiated by price or quality. Automobile companies make compact cars and luxury sedans and everything in between. Airlines sell coach, business class, and first-class tickets. The butcher shop sells everything from ground chuck to filet mignon.

Naturally, you’d like to sell as many of your higher-end (more expensive) products as you can. If you recognize that a customer is interested in one of your products, you can often entice them to buy one that’s a little higher grade. This is known as upselling.

Upselling works because you already have a willing purchaser. The customer has already become resigned to paying a given amount for a product. This allows you to focus the customer on the difference in price between one product and another.

A customer may not initially be inclined to pay $16.99 a pound for filet mignon. But if that customer is already inclined to pay $12.99 a pound for a strip steak, you can focus on the relatively small $4 difference.

The automobile industry understands this concept very well. It’s the reason that virtually every large auto manufacturer makes cars across a broad spectrum of price ranges. And the difference in price between one model and the next higher one is generally pretty small.

By understanding the past purchase behavior of your customers, you put yourself in a position to know how far up the product scale you can move them. You’re probably not going to move them from a two-door compact to a high-performance luxury sedan. But you may be able to move them from a two-door to a four-door.