Interview • 01.09.2010

Your own data base has dormant information that only needs to be dug up

Interview with Sylvia Detzel, Marketing Consultant and lecturer

Sylvia Detzel ist Inhaberin der Unternehmensberatung Detzel Marketing in...
Sylvia Detzel ist Inhaberin der Unternehmensberatung Detzel Marketing in Rutesheim bei Stuttgart.

Sylvia Detzel, owner of the consulting firm Detzel Marketing, lectures at the Dual University in Stuttgart on the subject of ”Data base systems, Analytical CRM and Data Mining.“ Is this hype or essential for business success? Where are the soft spots in companies, and what definitely needs to be done in customer relationship management? Sylvia Detzel delivers the answers in an interview with iXtenso.


You lecture on the topic ”Data base systems, Analytical CRM and Data Mining.” What is analytical in CRM and what is Data Mining?

Analytical CRM is one aspect of Customer Relationship Management. Simply put it is about gaining knowledge from the information that is contained in customer data. For this purpose, the gathered customer data – for instance the address or date of birth – and transaction data like purchase-, advertising,- or payment history is analyzed. Multivariate statistical methods are used here. One example for an application of this analysis method is Data Mining. Using Data Mining software, thus far unknown connections, patterns and trends can be identified by using a data base. So you do not have to “manually” work through a large amount of data, nor do you need to know beforehand what you are looking for, because the Data Mining- technologies virtually on their own comb through the data and search for previously hidden insights.


These sound like very sophisticated computer applications. Is this only a topic for large companies?

Let me say something first off: Fundamentally, CRM needs to be more than just a technology-focused consideration for a company, because living CRM means that the entire company needs to consequently be geared toward the customers! All business processes- starting with innovation management and complaint management all the way to an integrated communication – are systematically designed toward this goal. CRM itself is therefore not a question of business size. And as far as the application of Data Mining is concerned, it’s not the size of the company that matters, but the size of its data base. And it can definitely be significant in small and medium-sized companies.


Let’s be honest: Are CRM and Data Mining a new hype?

Customer care is truly nothing new. And the old wisdom that it is five times as expensive to obtain a new customer versus retaining an existing one, has been used for a long time. Today’s developments in the market environment certainly promote the CRM boom: IT makes data processing of large amounts possible – and with reasonable cost. Half a century ago a “data base” was still called a hanging file folder and in 1970 the relational data base system was mere theoretical in nature. Only by the end of the seventies was the hardware sufficiently developed to transform theory into a real product. At the same time, the consumer also changed his/her information seeking- and consumer behavior, and the development of ever smaller market niches made a goal-oriented sales approach away from the “watering- can- principle” necessary. Last but not least, people in charge at companies are faced with often humble advertising budgets – and all this while goals remain unchanged! This makes it urgently necessary to adjust measures more strongly toward individual product segments, customer needs and target groups. This is why I view CRM as a necessity and not hype.


Is there a benefit, provided the cost is justifiable?

At the start of implementing IT solutions for CRM there always needs to be a profitability consideration. It makes no sense to implement a solution that costs 1,000,000 Euros to tackle a problem that saves you 10,000 Euros per year.


What is a definite must in terms of customer relationship management?

The basis for customer relationship management is a carefully designed and well maintained data base. No matter which analysis tool you use, it can only be as good as the data on which it performs the analysis. At first this sounds trivial, but in reality it is one of the biggest problems. They say that on average per annum every tenth address is out-of-date. Ongoing address maintenance therefore is the top priority. It starts with defining clear recording guidelines for customer data, then making regular automated reconciliations and in the end it means – especially in the area of B2B addresses – that time and again you need to also manually take action. With a well structured and current data base you can perform a good analysis with simple means and use it for a target oriented sales approach.


...and what is the culmination in CRM?

The culmination is really the application of sophisticated Data Mining processes. You do not have to resort to “spacey“ processes like Fuzzy Logic or artificial neural networks. You can apply the cluster analysis for customer segmentation very pragmatically. A popular process is also the Association Analysis, which has a high practical use in shopping cart analysis. With it, you research whether there are individual items in a shopping cart which implicate the occurrence of other articles in a shopping cart within a transaction. Correlations in a purchase are revealed and purposefully used for advertising tactics. A classic application example is product placement in retail: If in 80 percent of all beer purchases potato chips are bought at the same time, then liquor stores will also place chips nearby. Online media for instance uses this knowledge to make recommendations and bundle offers.


Data Mining means gaining insights from existing data by smart linking. Data protection officers warn about consumers becoming too transparent. Should retail therefore keep its hands off?


No, certainly not! When you drive a car, you also know that you could be caught by a speed camera or get a ticket. Is the logical consequence then to stop driving a car? Most likely not. Instead you learn the traffic rules and obey them. Companies should deal with the subject of data protection the same way: Know the data protection legislature, obey it and also obligate all involved service providers through data handling contracts to comply, as well as maintain a transparent handling of data vis-à-vis the customer. Nothing can go wrong if you do all that.
And consider this: If you won’t practice customer care and retention, your competitor for sure will.


Your company does cross-medial marketing. What kind of customer information can you obtain through your own data base and through which advertising channel?

Data that you collected yourself is often the most reliable and above all most cost-effective. This is why you should utilize every customer contact for this – across all media. This means for example: using purchase order forms and inquiry forms, customer card application forms, phone calls, personal counselling interview at the POS or raffle cards. Often your own data base contains dormant information that only needs to be dug up – for instance through an analysis of transaction data or payment history. And here we have come full circle to Data Mining, but you cannot and do not have to do everything on your own. Address-providers can enhance your own data with all kinds of information.


If you could choose one contract, for whom would you like to create a marketing campaign and why?

Oh, that’s a tough one. Generally I like to work for medium-sized and frequently owner-operated companies. Usually you get quick decisions and you can really make a difference.
 

Interview by René Schellbach, iXtenso.com

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