To not only reduce the human involvement, but automated systems also remove the human error factor that holds most small businesses behind in the marketplace.

Here’s what I mean. The way automation has worked until lately is that a human constructs a process by hand, and then sets it to an automation methodology. That’s great as long as the data utilized is valid, accurate, and performs the hoped-for outcome. 

An example: Say your goal is to capture the prospective customer’s data by way of opt-in.  Then you’d like to understand buying habits of that particular individual, but how do you go about it?  Amazon is an excellent example of understanding shopper needs and desires based on prior behaviors. 

If you’ve ever purchased a book, pair of socks, or diapers, for instance, you’ll receive “if you liked this you’d love this” marketing messages in your email. 

But it doesn’t always prove to be true in its assumptions. I’m a regular shopper on Amazon.  However, just because I purchased a top 10 book that just came out does not mean I like to buy the top 10 books, which I receive email ads for. 

AI and predictive analytics are still uncertain technologies at this point, but they are getting better every day.   

But what happens when the data is corrupt in some fashion? What will the “automation” know about incorrect outcomes as a result of faulty input or malicious data manipulation?

These are the problems predictive analytics and artificial intelligence will solve in the coming months and years once it is refined.  As these new age processes become bullet-proof and reliable, accessible, and affordable, both large and small business will benefit tremendously.

The consumer will benefit immensely as the time spent researching and shopping online for goods they prefer.

I can only imagine that when real-time data input is measured against existing data files and matched along with it, the decisions the algorithm create, the more accurate they will become.

Like Amazon, B2C will gain the advantage over B2B based on the recorded preferences. For instance, you’ve researched upscale pots and pans. You then might receive an offer of two things, skillets, and cookbooks.

You choose cookbooks.  The very next purchase you receive, more cookbooks based on the part of the country you live (southern, Tex-Mex, Eastern Seafood).

The other is just the right seasonings to enhance those recipes contained within.  You choose the seasonings for crab, lobster, and other shellfish. The next time you receive an offer, it is for steam pots and cooking utensils like a shell cracker, butter stands, and upscale lobster bibs. 

And so the process goes. Predictive analytics and AI not only are learning from your purchases, but they also measure that data against similar demographics and psychographics of yours. The system inherently gets more and more on-target than the previous encounter with your brand.

If you are the purveyor of these types of products, you are learning about a very narrow niche of customer types. Armed with information,  you can drive your magnetic marketing messaging to them.

You’ll be able to learn more about individual customers based on their habits that are recorded in the data.  You not only are more accurate at your sales forecasting, but your inventory management, product mix, and ROI also become more predictable.

All in all, the real benefit of automation technologies just around the corner will be a boon.  Not only personalizing messaging to ideal targets, but it will also provide the opportunity to market to individuals that fit the predictive models AI and PA produce.

It won’t be long.  As a data scientist, I’m excited. 

For more information on how data can help your business, and how eLaunchers can ready you for this next wave of tech, click the button for a free consultation with me, Parthiv Shah.