Predictive Analytics is such a buzzword isn’t it? Analysis plays an essential role in all aspects of business, there is no doubt about that. Yet here we are, trying to figure it all out. Do we have clean enough data to make good and accurate decisions? Do we have the structure to track the areas in which we need to? These techniques offer decision makers the data to grow product, sales, do upselling, improve optimization and production, and execute on revenue forecasting to the executives of a company.
The smartest companies master the art of knowing who their customer is. They focus on who they are, why do they like what they do, what do they like, who and what helped them? When we begin to understand our customers, the fundamentals of predictive become much easier to track. For example: If I’m an online retailer like Amazon. I might have enough data about you to know: that you like shoes that are a certain brand, I know you like them at a specific price range, I know you typically shop on the weekends, and I know your preferred method of communication is SMS. As a retailer I might be able to send you a 10% off coupon on a Saturday night via text. Even better if I have data behind the type of shoes you like I could even send you 10% on those exact shoes you looked at last weekend. The chances of you converting and buying those shoes are much higher. This is why predictive is such a powerful way of meeting the needs of the customer. So why is it a buzzword? Because it’s the “future” it’s where everyone is trying to get to, the goal, the standard, the moment when you can say, “Okay, we made it!” The real trick becomes do we have enough data, how do we collect all that data, and where do we store it?
Now when you put this in perspective with customers this becomes even more powerful. Back when I worked for a Manufacturing company, they used Big data and predictive data to determine when to hit the ground hard with Marketing. For example: the auto industry knows when you might have a lease that is up on your vehicle, so they’ll run targeting campaigns to just those people. Or maybe you are like me and have got those telemarketing calls about the factory warranty on your vehicle being up. These are all examples of how big data and predictive data is used. We knew their income size, their demographics, geo, etc. We knew it all and could very easily target a group of people with a special offer in those specific geographies. Imagine if you could prevent a car owner from ever leaving the brand they 1st purchased? Talk about lifetime-value. What if we could prevent your customers from leaving before they even knew they wanted to? Crazy enough, in this world, this is not out of the realm of possibility.
There are various advantages to using predictive analytics to enhance the customer experience. Here are a few benefits:
- Minimize the amount of negative reviews or negative complaints which subsequently have a direct effect on the profit of the business.
- Minimize customer churn
- Decrease customer retention
- Predictive Analytics will assist the organization in identifying gaps with resources to better serve the customer
- Identify areas where customers run into friction points within marketing or sales and improve the process
It will help analyze the channels in which you are most likely to lose or win based on historical data and give you actionable insights.
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- The company has to be ready to provide a good experience across the touchpoints of their journey.
- They have to know the journey and know how to interact within those points
- They have to have some structured data (picklists, checkboxes, etc.)
- They have to have enough data
Taking moments within the funnel, flywheel, or even the customer buyer journey are where we are headed:
- predicting churn to run campaigns to prevent it
- predicting the likelihood of low NPS scores and running touchpoints to increase those scores
- Insights being delivered to tell you that adjusting your strategy within a channel will yield a certain outcome or result
Predictive analytics is definitely the future of Marketing, the real question is are you preparing yourself to capture the data you’ll need to do it?
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