How to Get Your Head Around Data-Driven Marketing

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How to Get Your Head Around Data-Driven Marketing

By Special Guest
Dan McDade, President and CEO of PointClear LLC.
  |  August 31, 2015

Earlier this year, the 2015 edition of the Marketing Technology Landscape Supergraphic was released. At that time there were 1,876 marketing technology vendors represented across 43 categories. That means there is a lot of choice, but also a lot of confusion. What do you need? Do you need any of it?

To set the stage for this article it might be helpful for you to know who is buying most of the new marketing technology options: financial services, software/Internet, government, communications and media and energy/utilities. These verticals represent roughly half of the spend on marketing technology. Most of that is in B2C. The average B2B company has a lot of data to look at before it needs to invest in software.

I often think, speak, and write about the fact that most companies ignore little data while focusing on big data approaches. According to a Harvard Business Review article: “The biggest reason that investments in big data fail to pay off is that most companies don’t do a good job with the information they already have. … Until a company learns how to use data and analysis to support its operating decisions, it will not be in a position to benefit from big data.”

In this article I’m going to recommend specifics that marketing decision makers should keep in mind as they evaluate their situation and solutions. I’ll break down data-driven marketing decisions into three areas: data sources, data analysis, and data optimization.

Data Sources

There is no such thing as a good list. According to a well-researched and well-written article by TOPO’s Sales Development Analyst Bryan Gonzalez: “Sales development organizations should use multiple sources for contact data. SDRs need contact data providers to allow them to find prospects, research prospects, and reach prospects by phone and email. … As a result, 89.9 percent of companies use two or more sources of contact data to fulfill the needs of sales development.”

I was talking to an industry contact recently about his company’s decision to create a very high- end (and expensive) quarterly magazine that was to be mailed to high-level executives at large companies. Unfortunately, someone in that organization made the decision to buy the cheapest list and sent the expensive magazine to 10,000 people – most of whom turned out to be not qualified. A prequalification test on as few as 500 of those names could have been completed for peanuts and would have saved this firm a ton of money.

On a weekly basis, I receive numerous offers for lists via email and voicemail. The fact that these pitches are going to the wrong place in our organization (and that most of the time, we are the wrong client for these offers) says it all.

So, the first lesson is: 60 percent of the value of a marketing campaign and subsequent data-driven analysis will come from the list. Acquire your data accordingly. Test first. Multi-source. Recognize that lists decline as soon as you buy them – so don’t buy the universe. Acquire a sample, test, and then acquire the lists as you can effectively consume them.

Data Analysis

Is your organization afflicted by analysis paralysis? If so, you are hardly in the minority. Today’s marketing solutions can provide minute details about your prospects’ visits to your website and the content they consume, but they also make it easier to send more poor-quality leads to sales faster than ever. Before you start dividing your prospect universe into subsets – and, before you develop a persona/content strategy that’s so complicated it’s almost impossible to deliver on – establish benchmarks around the following metrics:

• percentage of leads passed to sales that meet the universal lead definition (If you don’t have one, you’re not alone, but start working on this immediately.);

• percentage of qualified leads sales accepts;

• percentage of leads accepted that become sales qualified (hit the forecast);

• percentage of leads that become closed business.

Marketing has developed a cost per lead mentality. And while that’s not totally their fault, to be relevant to sales they have to step up the game and deliver quality – not quantity.

Data Optimization

Most of the marketing campaigns I see ignore two-thirds of the value of running the campaign. At the same time that you identify 50 highly qualified sales opportunities (out of a universe of 1,000, for example), you could generate another 100 or more leads by effectively working what we call pipelines, nurtures, and even unresponsive (to the first touch cycle) dispositions.

When you start to pursue a data-driven marketing approach, use the return on little-data-driven marketing activities to pave the way to big data projects – if and when it makes sense.

Dan McDade is president and CEO of PointClear LLC.




Edited by Maurice Nagle
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