How to Do Analytics Quickly and Cheaply

For most of us, making a clear connection between what we do and business performance seems like a bridge too far. It’s much easier to focus on whether the program fulfilled its intended purpose—e.g., number of white-paper downloads—than it is to try to determine whether that white paper had any direct impact on a sale.

ITSMA is beginning an in-depth research program into analytics (which we define as analyzing data to inform decisions, predict buyer behavior, and forecast trends) to develop a set of simple analytics best practices for B2B marketers that don’t involve installing gobs of technology.

We’ve just completed a survey on analytics. I’ll be revealing some of the highlights of the survey at our December 16 online briefing, What You Need to Know About Marketing Analytics.

Two top experts will be joining me online that day: Pat LaPointe, who is managing director of a consultancy called MarketingNPV, which advises marketing executives on how to develop marketing metrics and analytics programs; and Samir Bagga, vice president of global marketing and communications for Satyam.

Using his own experiences at Satyam, Samir will discuss how marketers can partner with finance organizations to help create a bridge between marketing data and financial results. He’ll answer questions such as: Do you need a financial analyst permanently assigned to the marketing department? What other mechanisms can you set up to make the connection with finance?

Samir will also talk about how Satyam prepares in advance of launching a new program to be able to measure its impact. With so many different things going on at once, it can be difficult to figure out which of the four things you’re doing with customers at the moment is making the biggest difference.

Meanwhile, Pat will give us an overview of the kinds of data marketers should capture to do effective analysis. He’ll also talk about how marketers can get effective analytics programs up and running quickly and easily, without installing a bunch of complex technology. As a preview of some of the things you can expect to learn at the briefing, I’ve excerpted some of Pat’s comments from a recent interview I did with him:

ITSMA: Pat, I think many people confuse analytics and metrics (I know I do, anyway). What’s the difference?

LaPointe: Analytics is a process by which data is assessed from a variety of perspectives to try to generate specific insights or to try to predict what might happen, given a historical pattern.

Metrics are key indicators of either diagnostic or predictive value. So, for example, one might perform analytics on a large volume of historical customer transaction data to identify which customers buy which types of products and services. But with metrics, one might be looking at that data to see whether or not the percentage of customers who are spending more each month is increasing or decreasing, for example. So, the metric might be customer value evolution, and you might be looking at the index of customer value evolution on a rolling, three-month basis at any point in time.

You use metrics to help you assess the ongoing health and quality of your business. You use analytics to help you answer specific questions about what seems to be driving outcome, and you can use analytics to periodically recalibrate the metrics that you decide to pay attention to.

ITSMA: What’s missing from most analytics programs today?

LaPointe: One key factor is a lack of clarity in terms of how the programs we’re running are expected to ultimately transform into economic value. For example, if we’re running a program on customer retention, we capture only the middle ground of whether we retained customers. We don’t take it farther to determine whether that was the most profitable way that we could have spent our discretionary dollars.

Another factor is that we have so much going on at once that it becomes difficult to determine the specific effects of any one program.

For example, a marketer may decide to try to improve its channel partner program by launching an online university for channel partners and distributors. A program like that can often take months before the impact of better-trained channel partners begins to show up in terms of either the number or pace or velocity of new customers being added, or changes in the end-customer buying behavior that are more profitable. In the interim, other things might have happened: direct marketing campaigns, advertising campaigns, new sales incentive programs. After six months no one is really sure about the net contribution of all of that time and money invested in improving the channel partner program.

ITSMA: How can you separate the impact of one program from another?

LaPointe: I’m a big fan of experimentation, of trying something out on a limited basis before rolling it out everywhere. Lets go back to the online university for channel partners. Instead of diving in and spending all the money at once, maybe we start by developing a representative sample of channel partners and roll it out to them to see what impact, if any, it has on sales.

The good news is that this doesn’t require high-end statistical modeling techniques. However, it does require a little bit more money or time and attention. But the amounts of money and attention that we are talking about are fairly negligible compared to the amounts of money that are spent without any clear idea of what kind of return is expected. Nor are they large compared with the amounts of money that are cut from budgets after no credible evidence has emerged that there has been an impact.

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