Avoid Conflict of Interest in Your Data Supply


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Eliot Spitzer, attorney general of the state of New York at this writing, wasn vigilant against conflicts of interest in the financial world. He imposed massive fines on American banks for allowing their investment banking departments controlling a flotation to unduly influence the analyst buy/sell/hold advice being punted out by their share-broking arms.

All this might seem distant from the world of CRM and responsive marketing. But conflict of interest is not just a matter for the financial markets. In fact, the subject of conflict of interest has increasing significance for us all today, the more so because hidden conflicts can suppress marketing performance to a level that can cause massive financial shortfalls for your business.

All markets are becoming increasingly competitive and fiercely contended. According to recent research from Group 1 Software, customer churn is actually increasing—even in the traditionally more stable world of retail banking. At the Lloyd James Group, our research shows that the market for available data is gradually tightening.

As consumers, we are much more savvy nowadays about giving away information on ourselves (we’re prepared to do so but only if we get something in return). And the legally available communication channels for unsolicited marketing have also been restricted by European Union and national legislation. All of this means that the adverse consequences of campaign under-performance have quietly become very serious, indeed.

High-performance responsive marketing activity relies on high-quality data. This is true, both for accurate, relevant and up-to-date information with which to acquire new customers and for information on existing customers that enables relevant and appropriate up-selling or cross-selling offers to be put their way.

Mystery shopping

It is not only the crossover of data supply and analytics which can cause conflict. Another area to look out for is with mystery shopping and agency. The delivery of a campaign and the analysis of those results should surely be independent form one another.

Several years ago, a dealership employed its marketing services company to carry out the analysis of customer experiences through mystery shopping. The mystery shopping exercise established the need for better training and more skilled customer service staff. The mystery shopping company, which also had its own training academy, convinced the dealer that it needed to spend several thousand pounds on improving training levels. The dealer was also persuaded to employ part-time staff€”from the agency€”to carry out a new campaign and aid the performance of the permanent staff throughout.

Six months later, the marketing services company pulled out its agents, stating that the training process was now complete. A follow-up mystery shopping exercise celebrated the success of the campaign and concluded that the training and performance levels had exceeded all expectations.

In total, the analytical service and campaign delivery cost thousands of pounds. However, when it became clear the campaign and extra resources did not yield any further sales or revenue, the dealership decided to employ an independent third party to measure the campaign performance again. It turned out that, indeed, the sales performance levels had not improved at all. The exercise resulted in a huge loss for the dealer. Furthermore, the marketing services company suffered a very bad reputation and shortly afterward went out of business.

—Lynn Stevens

The most powerful proof point underpinning the drive toward data quality is figures from the Direct Mail Information Service, which show average campaign volumes virtually halving between 2001 and 2005. Given that budgets continue to be transferred from above the line into direct marketing, we have to conclude that campaign performance (in terms of conversion to sale) must have improved to compensate for the reduction in volumes. After all, marketers are hardly going to tolerate a reduction in business performance from their campaigns—on the contrary, they are under pressure to improve provable business results.

So conflict of interest must not be allowed to creep into data supply.

Creeping consolidation

Where is the potential conflict of interest coming from? Creeping consolidation in the marketing services industry is the likely culprit. Up until 10 years ago, the industry was composed of many specialist suppliers of different services. Since then, there has been a movement to bring these various parts together under one roof to provide client companies with a one-stop-shop service. In many ways, this idea made logical sense. Customer analysis could feed strategic thinking but also be made to face the practical realities of campaign execution. The disjoint between great analytical insights—or brilliant creative ideas—and the practical follow-through has been well documented. And while companies are rapidly overcoming barriers to economically viable mail segmentation, we still hear of horror stories where ultimately completely impractical strategic initiatives are promoted at board level (or even to the city) before they crash and burn.

Consolidation between analysis and data, however, is a flashpoint of concern about potential conflict of interest.

An important distinction needs to be made. There is nothing wrong with a broker conducting analysis and then applying the insight to data selection and purchase. That is because brokers have access to pretty much all the available data sources, with a vested interest in no particular one. If the marketer—the person who engages the broker—is going to come back for repeat business, then it is in the broker’s interest to ensure that the marketer gets the best-performing data. On the other hand, we should treat with extreme caution data


who also offer analysis and insight.

This point merits further explanation. There are two aspects to the analysis-data conflict of interest. The obvious one is that analytical outcomes may be interpreted in a way designed to play to the advertised strengths of the datasets the company has to sell. This is obviously such a clear and present danger that the majority of marketing professionals would be on the alert over the possible conflict. Nevertheless, marketing buyers in this situation should be very careful to always invest in a test dataset from another data source to regularly benchmark response and conversion performance.

Favored dataset

Less obvious is the mirror-image situation, namely where a favored dataset skews the analysis in the first place. Marketing analysis relies heavily on randomization and “representativeness,” if it is to deliver accurate and useful insights. Take the example of a retailer profiling its customers and then looking for areas where people are heavily represented. If the analysis is based on data that is not representative of the balance of consumers in the areas in question, then it becomes impossible to apply the profiling to viable strategies. Even if the profiling is accurate, the area penetration analysis may not be. And this kind of analysis is often used not just for campaign planning but also for store siting and stock management. Get it wrong, and we are talking about literally millions in revenue at stake.

Even if you trust your marketing services supplier, you should still demand proof of probity in any areas where you think a conflict of interest might occur. It is important that everyone—clients and suppliers—work toward complete transparency on this issue. The CRM and direct marketing industries have made major improvements over the last 10 years, both in terms of efficient use of marketing budget and in terms of an improvement in consumer receptiveness to direct marketing through better targeting and data quality. That situation can, and should, improve still further, but conflicts of interest at marketing services conglomerates must not be allowed to undermine the positive trend.


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