• by Suresh Vittal , Columnist, March 6, 2018

Imagine you and your colleagues gathered an unprecedented amount of information in preparation for a meeting with a prospective client. You know their product preferences and corporate priorities — maybe even what they ate for breakfast. However, when you enter the meeting, suddenly no two people on your team can speak the same language. Closing the deal would be nearly impossible.

Sales and marketing departments face a real-world version of this nightmarish scenario every day. Data from the sales team might be structured differently from that of the marketing team, making it difficult and time-consuming for these departments to share insights about a given customer.

Fortunately, businesses can leverage today's latest artificial intelligence (AI) technologies to translate data into a common "data language." This enables companies to spend less time trudging through mounds of data to derive insights and more time developing and executing personalized experiences at massive scale to optimize the consumer journey. 

Despite the hype surrounding data-driven marketing, many companies haven't taken full advantage of the information they collect on their consumers. According to the consulting firm McKinsey, nearly 60% of sales departments admit they aren't using data analytics effectively. Companies already have the information they need to pinpoint customer preferences, develop new products, and make better decisions; they're just not using it effectively. One major challenge, as the study notes, is the prevalence of "siloed data within a company."

These barriers to information sharing are perhaps most pronounced between sales and marketing teams — two departments that generally use different technologies to collect and analyze consumer data. Since these technologies tend to structure data differently, bringing sales data to bear on marketing analytics (or vice versa) can require hours of work translating data from one format to another. This can be detrimental to a company on several fronts:

•Productivity: One Forbes study found that 80% of the work done by data professionals involves preparing data, leaving less time for other work.

•Customization: The inability to customize customer experiences in real-time can lead to delivering irrelevant or repetitive content or ads, which frustrates consumers and makes them less likely to patronize certain brands.

•Leads: Time is of the essence when it comes to following up on sales leads, which means potentially lucrative sales leads could go cold while data is prepared.

However, it's now possible to apply AI to the task of unifying a company's consumer data. Specifically, firms that use AI to automatically translate their data into a common language will be able to instantaneously track consumer behavior, preferences, and interactions across the sales and marketing departments, gleaning valuable insights along the way.

It's time for companies to unlock the full potential of data analytics, and give their consumers the unique, personalized and engaging experiences they have come to expect. By speaking the same language, marketing and sales teams can ensure their messages don't fall on deaf ears.