Make CPG Database Marketing Practical

The New Economy mantra that the “Internet changes everything” is not fully true yet for marketers of consumer packaged goods. For the most part, they have yet to use the Web to create a database marketing system that builds on established incentive programs.

Traditionally, CPG manufacturers have been frustrated by the high costs, lack of measurability and small rewards that come from offline database marketing programs.

The Internet has only offered options such as banner advertising and portal sponsorships, which have proved to be ineffective. Sometimes this is the result of existing interests – sites created by larger offline companies seeking to protect their core mass-market business models.

In other cases, site builders do not have the knowledge base to create a CPG-oriented solution. This solution will ultimately come from CPG marketers, which need to make a cultural shift to fully think and live database marketing, and site developers, which need to realize the needs of the CPG industry.

The cultural shift includes the following:

• Moving cases to acquiring customers: Under the database culture, a brand manager will ask, “How many new customers did I acquire?” and “How many did I lose and why?” just as often as “How many cases did I sell?”

• Dealer-loading to pantry-loading: Database culture uses promotions to build repeat and lifetime value. Rather than pumping dollars into mass-distributed coupons, database marketing can be used to build “pantry inventory,” not store shelf inventory. And the greater the pantry inventory, the higher the likelihood of building habitual use.

• Changing attitudes to changing behavior: Database culture is one of measurement, unlike the mass advertising model, which just builds brand awareness. Database marketing allows you to measure, adjust and redirect your efforts to acquire customers and drive sales – something you can take to the bank.

• Share of market to share of profits: Database marketing allows customers to be rated. This identifies loyal heavy users and high-maintenance switchers that will buy only with a discount. Manufacturers can then custom-target incentives to optimize profitability.

• Measuring results to using results: Database culture insists on micro-basis results, down to the household level in some cases, which can be used to customize relevant programs. It refutes the mass-marketing model, in which results are measured on a macro-basis with no hard data that can be re-applied against specific targets.

Web developers need to do their part to design a system for CPG manufacturers that includes the following elements:

Use coupons offers as the reward for purchase. Don’t totally eliminate coupons – the most effective way to build trial – amend them and offer them through the Web. Combine the incentive of coupons with the database-collection opportunity of rebates and the ability to change offers quickly and easily.

New offers must be available weekly or even daily. The average family purchases food 16 times in a single month; therefore, the ideal system must be updated frequently.

The offers and Web site should be easy to use. Clipping coupons is time-consuming. Web offerings must be time efficient to eliminate handling individual small offers.

The system must be able to capture and use actual data: who, what, when, where and how.

Research has shown that nearly 90 percent of consumers are willing to provide personal data in exchange for saving money. It makes sense to use the Internet to fully capture this information and use it for the targeting of future offers. A good site will help manufacturers incentivize, build loyalty and also provide priceless information about customers.

Eliminate unnecessary middlemen. What if there is a way to eliminate the retailer as middleman altogether? Cashiers’ jobs depend on their ability to keep lines moving, so there is little regard for carefully examining coupons.

Proper redemption leads to huge consumer selection. The site should be made with proper redemption in mind. Fraud-proofing a site will lead to increased manufacturer support, offers and visitors. The ideal system must control the number of offers that a household can use in order to prevent brand de-valuation and permanent price reduction.

The product, not the offer, must be the hero. The site has the opportunity not only to make an offer but also to further brand the product.

Manufacturers know that the more your brand is simply listed with savings, without

reinforcing the brand message, the more it is commoditized. The ideal site includes the brand promise, as well as the savings.

Offers must be usable at any store on or off the Web. Research has shown that 73 percent of shoppers compare prices at various stores, and the majority will go to multiple stores to find the lowest price. Also, even though a small portion of packaged goods sales are online, a Web system such as this would be used by the most attractive demographic – e-commerce shoppers.

The site must permit you to have offers available at the time the consumer is ready to buy. Most sites charge manufacturers distribution costs or an up-front minimum fee against actual redemptions, forcing manufacturers to filter programs with long hiatus periods. Internet database marketing should not work that way, since all major costs are shifted to the back end, as with free-standing inserts that allow manufacturers just-in-time offers ready to meet purchase interest.

The system must be free with no hidden charges. Savings alone should be sufficient to pay for these offers, without making consumers pay for their savings.

And here are five final criteria for evaluating the best database system:

• Continuity of users (membership systems are best) to build lifetime value.

• Behavioral and demographic targeting. Look for full decision-tree functionality, including treating buyers differently than non-buyers – and the ability to pantry-load.

• Ability to isolate the most profitable consumers.

• Real-time reporting on intent and actual purchase.

• Knowledge on users, market basket data and competition.

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