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  • admin 9:51 am on March 27, 2015 Permalink
    Tags: Disruptive, ,   

    So You Want to Be Disruptive? Not So Fast. 

    magnifying glassSometimes, it feels like businesses know us better than we know ourselves. We let Facebook pick our friends and Twitter filter our news. Google knows where you’ve been and Uber knows where you’re going. All of this customer knowledge is driven by data analytics tools, but even the best analytics can get off track if companies lose sight of what their customers really need from them.

    There are three kinds of analytics that fuel data-driven marketing today: prescriptive analytics (What do my customers want today based on past behavior?), predictive analytics (What will my customers want tomorrow?) and disruptive analytics (What do my customers not even know they want yet?). Although we tend to think of the last two types as the most innovative, the reality is that innovation isn’t always about guessing the next step, especially if that step takes you further away from your customers.

    You can innovate by being prescriptive. For example, a retail store might “video scan” customers (with their permission) as they enter the store and match that image with the customer’s profile to make product recommendations based on past purchases.

    You can innovate by being predictive. A financial services company, for example, might analyze social media in real-time to measure consumer sentiment as a predictor for stock market shifts.

    You can innovate by being disruptive. Uber is a good example of a business that artfully combined different strategies—crowdsourcing, mobility and data analytics—to disrupt what had become a staid industry (short-distance transportation services).

    Trying to be innovative at everything won’t work, and choosing to disrupt a market where you have long-term customer relationships may lead to swift and negative consequences. Businesses need to align their data analytics around their brand and their customers. The right strategy could be getting closer to your customers by using your intimate knowledge to serve them better, or it could be driving a wedge between dissatisfied customers and the companies that underserve them.

    One best practice we’ve seen from successful companies is the separation of different analytics initiatives. Prescriptive analytics are commonly aligned with a data warehouse since they draw primarily from historical and transactional data. Predictive analytics might focus on massive amounts of external or semi-structured data (e.g., social media posts, weather data), and thus be a better fit for a big data project. Disruptive analytics might be assigned to a team of data scientists using complex and proprietary algorithms on yet a third platform (e.g., a data mart).

    These islands of insight need to be brought together, and marketing applications are the ideal place for that convergence. When businesses can boast both a 360-degree view of customers and a 365-day view into their past and future, they’ll be in a much better position to enrich the customer journey.

    The post So You Want to Be Disruptive? Not So Fast. appeared first on Darryl McDonald: Vision 2.0.

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  • admin 9:45 am on February 14, 2015 Permalink
    Tags: , Disruptive, ,   

    The Rise of the Disruptive Data Warehouse 


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