Is artificial intelligence the best thing to hit the marketing scene since social media? Considering all the buzz about it, especially lately, it might just be. But is it really such a great tool for marketers, or is it just the idea of the month and soon to be forgotten?

It’s not likely that the fuss will die anytime soon, and there is a good reason for that. AI has lots of different applications across the technological spectrum and many businesses are beginning to take advantage of this.

An interesting example is the AI-powered virtual reality tech Lowe’s is currently experimenting with in collaboration with Microsoft, that will allow shoppers to digitally design an entire virtual kitchen in the store, before making a purchase.

But best of all, AI has the potential to give marketers what they want most – data, and loads of it. And let’s be honest, data is the most precious commodity of all.

If that was all AI could help with, it would be enough. But it also makes the analysis of huge amounts of data possible in record time, facilitating highly accurate, data driven marketing campaigns.

We are not in a position where we can leave everything to the computer, though – machines are a lot cleverer than they were, but they are not quite smart enough to take over, yet. But that really says more about the developers than the software itself.

Many programs are pretty effective already but subject to biases on the part of the developers that created them. Our data source integration is also not perfect yet. The problem is that many data sources don’t work well together.

Extracting meaningful information from such a varied set of data sources is extremely difficult. It is going to require skill and a lot of intuition on the part of an AI program to be able to figure it out. And, while machine learning has improved by leaps and bounds, it is not quite there yet.

Make no mistake, though; the time will come when it will be possible. All you need is a great analytics platform that is able to extract meaningful data from various sources, disregard whatever is superfluous to requirements and start to identify patterns within it.

Think of it as a platform that would review all the data available and be able to determine what was relevant or not. Kind of like a scientific review paper on a range of different studies. Except that the scientists drawing conclusions from the amalgamated research would be AI.

Say, for example, that Walmart wanted to market a new product. It could set an AI platform to analyze data sets from related products, buying trends in the field, client disposal income, etc., to come up with a picture of the ideal end user.

What’s more, AI could be used to subdivide the target demographic and create targeted, personalized sub-campaigns. It could analyze buying patterns and determine the optimal launch times, and create offers targeted at increasing customer spend. With AI, it would be possible to do in-depth analysis that wasn’t possible before.

AI also makes automation of tedious, repetitive tasks a lot easier. It gives executives the information they need to make the right decisions in real time. Say, for example, that a marketing promotion is tanking. Analysis of data in real time would enable a fast shift in position, minimizing potentially expensive marketing mistakes.

It can also help to reduce some of the drudgeries of marketing processes. Automation can be applied to repetitive or boring tasks that do not require a lot of mental power. This can free up staff to do more valuable work – like building client relationships, for example, or going out and meeting new clients.

Then, of course, there is the real life impact that AI can have on our client relationships. Something as simple as a chatbot program can transform the client’s interaction with the company.

Chatbots can be set to answer client’s questions intelligently, to boost sales, and to gather as much potential data as possible. The bots can learn from each interaction and so boost the client’s experience in much the same way as a good relationship with a salesperson can.

The bot could, for example, ask what the client’s favorite color is, what her measurements are, etc., and record that information in the client’s file. This gives us more information to work to create even better targeted campaigns in ways that could be quite creative.

Let’s say that the client’s favorite color is green, for example. You could use this information to sell her a pair of green sneakers, for example, but what if you take things a step further. What about tailoring her marketing promotions so that the color green is prominent.

Say you send her a coupon, for example, why not make it green in color? There are obviously more complex items to consider here, but AI would make it easy enough to customize each person’s offers with that level of detail in mind.

And, as we know, the better targeted the campaign, the more chance it has of striking home and being successful.

More information: https://www.16best.net/blog/how-brands-use-ai