Doing marketing is an art. It is a delicate choice of timing, approaching method, and content based on empathy.

The path is long, from a description of a product or a service to a list of offers signed by newly acquired customers.

Let’s start our journey with you. Your company is B2B, produces appliances for shops used for entertainment and advertising.

Your product is a device connected to the internet that automatically selects the background music and images and alternates them with the advertising images/spots of the shop using a specific algorithm. It is in front of you, a demo item over there on the table. In your email, a PDF file contains capabilities. The product’s marketing strategy has already established the target customer sector, the price, the free and paid options, etc. You have already a set of loyal customers that have tried it, and they were so happy that they had released great interviews for feedback.

The first automation

You collect the customer categories that could match the customer sector, a vast meaningless list. Injecting some AI on that list would pop out a new sorted classification with a predicted sequence, and the first categories now appear appropriate to start your campaign.

Furthermore, hierarchically comes out the classified prospects. The prioritised list matches the criteria of the customer sector, sales history, distance, and others. You can quickly sort them out for each metric and choose where to start.

Exciting!

A further improvement

Your team now is ready. Your colleagues have prepared the material for each social network, the script for the telephone calls, the SMS strategy, and the email content. It is time to make the calls.

When you select the subset of prospects to get in contact with, another automation comes to give you additional information.

From the presence online, AI extracted the number of followers and the number of published contents per social network, the most used words in posts, the most used words in titles, and other valuable data. The automation shows the best matching prospects compared with your advertising material’s content, creating a metric that you can use for sorting.

When your good job produces…

unexpected results

The team proceeds to contact the prospects. The information for each of them get more detailed the more you reach out to the candidates using all the channels.

Another nice feature of automation is the adaption of growing information. The metrics vary with the information you store. The value of the prospect is weighted to adjust the classification and the expected success rate.

When you cannot sell now your product because the customer needs a proper purchasing time window, or the customer has already bought a similar product from the competitor, the automation come again to your help.

Along with the adaption of parameters, AI also calculates the better matching products/services by another metric. This information opens the opportunity to acquire customers by selling adjacent products.

Conclusion

This first episode of our journey in visiting the ERP functionalities empowered by Artificial Intelligence shows the enormous difference with what nowadays is in use.

On the other hand, you can realise almost the same result even using a fine-tuned BI, even if it requires a significant effort.

Nonetheless, this implementation centralises automation’s potential with a shared strength with no rivals compared to conventional calculations.