This article will provide some sound advice about getting data-driven marketing right—from think big but start small (and with the basics), to take an action-based approach, pick your battles, beware of small sample sizes, and more...

1. Start with the basics

It's easy to become obsessed with pinpointing the ultimate ROI-based marketing metrics; but, rather than hunt for 'the killer' indicators, it's best to identify a few easy-to-implement, basic metrics that can provide a sound assessment of both performance and ROI.

Those can include number of leads, number of Marketing-qualified leads (MQLs), number of MQLs pending sales review, and the number of MQLs recycled/accepted. All of those will give you an idea of how to ensure leads have the proper number of touchpoints to be qualified and get to the right salesperson for conversion.

2. Think big, start small

Your data-driven strategy should be a combination of small wins and long-term goals. For example, it's relatively straightforward to track the conversion of leads into opportunities. It's much harder to track the ROI on search engine marketing campaigns if you want to track ROI all the way to closed deals that were touched by 10-20 different campaigns.

Both are important, so get your quick wins where possible and recognize that other data points will take much longer to realize.

For example, in search engine marketing, you will need to tie Google, Yahoo, Bing, and others to your website to begin, then connect your site with Marketo, Salesforce, and your data warehouse. After that, you'll need to do attribution across marketing campaigns. There are various places where tagging and data sharing can go wrong, so be prepared—and allocate time for setbacks.

3. Take an action-based approach

It's easy to come up with a wish list of data... and much harder to find actionable data. All too often, a marketing analysis will take days of crunching numbers, only to discover that there is no smoking gun or major opportunity to optimize the business. The best data-driven marketers will find ways to minimize the time they spend "exploring" data and accelerate their time-to-insight.

When you're considering the data you want to analyze, ask yourself two questions:

  1. If I had this data regularly, how could I improve my efforts? If you can't answer, there is probably a better analysis to run.
  2. What is the quick-and-dirty version of this analysis? If a cursory analysis of the data doesn't yield much, it may be an indicator that the data isn't as important as initially thought—or, at least, not as actionable.

4. Pick your battles

There will always be an infinite number of metrics you can analyze; but, most often, less is more. Whatever the major needle-movers are for your business, put 80% of your effort into optimizing those rather than trying to focus on every possible metric.

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Eight Rules for Data-Driven Marketing

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ABOUT THE AUTHOR

image of Ashley Stirrup

Ashley Stirrup is CMO of Talend, a leader in Cloud and Big Data integration solutions.

LinkedIn: Ashley Stirrup