From Data Science to Data Strategy

InsideView CEO Umberto Milletti offered three marketing themes for 2016.  The first two, Sales and Marketing Alignment and Data Driven Messaging and Targeting, have been well discussed over the past few years.  It has long been clear that sales and marketing need to work together and that data should be driving the marketing function.  The new idea for 2016 is the elevation of the data scientist into a strategic position in the company.  According to Milletti:

If 2015 was the year of the data scientist, then 2016 will be the year of the data strategist.

We’re in an explosion of sales and marketing technology, and every system relies on data. The more data you have, the more important your ability to update and sync that data becomes. Companies are consolidating systems and that is driving the need to implement a strategy for customer data that resides in multiple places. Otherwise, you get silos of customer information.

Good data strategy considers the flow of information, the accuracy of the data, and the consistency of the data. To do that well requires someone focused full-time on a company’s strategy for their data.

This is why the title “Chief Data Officer” seems to be more popular with search frequency trebling over the past three years on Google Trends:

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Google Trend for the search term “Chief Data Officer”

Data quality, an element of broader data strategy, is becoming increasingly important.  While the statement “garbage in garbage out” goes back decades, marketers long allowed their databases to go stale.  Many marketing databases are rife with out of date contacts, incomplete or inaccurate firmographics, and undeliverable addresses.  With predictive analytics and big data, the ability of these systems to provide insights is dependent upon the underlying data quality.  Data quality is also required for tying together historical data silos which have employed different standardization rules and identifiers.  Pulling together all these elements requires an enterprise owner of data strategy.

If your company isn’t ready for a broad data strategy, you should at least consider implementing data quality practices in your CRM and Marketing Automation platforms.  Several vendors including ReachForce and NetProspex are developing ongoing data quality solutions that synchronize data across multiple platforms.  These systems verify and standardize global address, validate emails and phones, manage duplicates, and enrich platforms with company firmographics.

Another important feature is web form verification which matches prospect records against their database and performs real-time validation of entered fields.  Not only is data validated at time of entry, but the number of required input fields can be reduced, resulting in a lower web form abandonment rate and higher ROI for your digital marketing investments.

NetProspex Workbench also offers Dun & Bradstreet linkage, D-U-N-S Numbers, emails, direct dials, and tech platform variables (products and vendors).

Although InsideView doesn’t offer lead verification tools (e.g. phone, address, email), it supports match and enrichment for a broader set of CRM and marketing automation platforms.

Keep in mind that data quality not only benefits your marketing though better targeting, segmentation, and lead scoring, but it also provides value to your sales function.  By infusing leads with broad firmographics and linkage, you are more likely to be passing actionable leads to your sales team and routing them to the correct sales reps.  Furthermore, when leads are mapped to sales intelligence platforms, reps can quickly qualify them and begin planning account messaging.

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The NetProspex Workbench Data HealthScan report provides a free PDF detailing pre and post enrichment field population rates, data error rates, and segmentation reports.

InsideView, NetProspex, and ReachForce are all cloud based solutions with low barriers to adoption.  They also include data health analyses, segmentation reports, and integrated prospecting as part of their feature set.  So even if you cannot implement a global data strategy across your enterprise, sales and marketing can begin by focusing on a solution which improves the quality of their leads, contacts, and accounts.

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