Selling is a profession with which only a few people can deal. It is frustrating. A sales manager gets so many Nos per day like every other person in an entire year. The good ones know that the low number of Yeses bring the prize, the commission. That’s why they focus on them. They crave the Yes.

The best friend of the sales manager is ERP. It is perfect for collecting all the information regarding the customer and recovers the historical data precious for understanding the type of customer.

The best tool for converting their time into commissions.

Improvement in data collection

When the marketing team prepared the prospects to contact, AI helped them collecting metrics regarding the presence online. Not only. Having scanned the contents, it created statistical data referring them to the most worthwhile words connected to your products/services. You can even search inside the scanned content and tag specific words or sentences or web pages as most important for focusing during the selling phase.

Together with the tags you associate with the customer, the automation suggests the best matching product/service, and you can refine that association by your knowledge of the customer. The machine learning feature will adapt the association’s algorithm, the more you perfect the relations between content, words and products/services.

Template, which to choose?

The content for communications to the customer is a delicate part during the selling phase. It would be best to prepare it with the most refinement you can, without wasting too much time overrefining.

For every moment of contact (the first call, the offers’ presentation, the latest products’ presentation, etc.), you have already a template. Nonetheless, most of the times, you rework it because you know something in particular regarding that customer. The machine learning feature collects the templates you have already edited and helps you. It predicts the best to choose by similar parameters between customers.

Top of mind strategies

A sales manager knows the best moment for calling a customer, can manually add to the calendar reminders. Or better, somehow get the benefits of automated procedures. Like, prepare the template that the automation will send on a specific date using a particular channel.

With this potential, the strategy becomes a structured and levelled set of templates. Let’s make an example of real-world usage.

Suppose you know the customer’s birthday. In that case, one month before that date, the automation can send an email with a voucher for a special discount templated with the season theme and retrieving promotions running at that time. Maybe one week before AI can send an SMS for reminding the customer about the voucher and, at the same time, add to your calendar a reminder to make a birthday call. The automation can detect if the customer has redeemed the voucher. In that case, it can send a satisfaction survey after some days of receiving the product/service. On the other side, it can send another email reminding the voucher and notifying newly published promotions.

Conclusion

The journey moves towards selling. We have explored the way a sales manager can benefit from machine learning. And we have understood that the algorithm improves the more the user refines the connections between content and tagging.

A sales manager can potentially use global information, online presence, and social networking. Depending on the ERP, manually or by automation.