B2B sales organizations are full of customer data. CRM, ERP, Ticket Systems and Web Shops are just a few of all the data sources that are analyzed in account management today in order to Sales Decisions to meet. Each piece of information tells a different important story. The challenge in sales management is to bring all the data together in order to identify risks and potential in the customer base in good time.

The Limits of Excel and Business Intelligence

Excel and Business Intelligence Dashboards are at the forefront of sales management tools. Monthly exports from CRM and ERP, pivot tables, and beautiful bar charts should help to derive the right actions for sales. Even though these sales reports are visually impressive and convey a sense of “transparency,” they only ever provide a glimpse of a specific period of time in the past.

Despite everything, sales reports are still considered extremely important. So teams waste around 1 day a week With the analysis of Excel tables and drill-downs in the BI dashboard to understand

• Why sales fell last month
• How many products customers buy on average and
• Which account still has potential.

In addition, with the volume of data, only a fraction of it can usually be analyzed and understood in depth. In the end, there is often no time at all to look ahead.

Prescriptive analytics in B2B sales

Artificial intelligence is increasingly conquering the B2B sales management market. With the help of AI-based data analyses, sales teams can keep track of all customers — and do so fully automatically.

Prescriptive analytics tools not only analyze a specific period of time in the past, but also link all relevant data in one place and analyze the entire customer behavior. In this way, sales teams are constantly informed about the most important sales opportunities and risks from all customers.

Scattered data is thus turned into concrete sales campaigns. This eliminates the need for days of analysis in Excel chaos and drill-downs in BI dashboards. Sales managers once again have more time for team enablement and strategic concepts. And account managers are always with the right customer at the right time to prevent migrations and exploit potential.

Conclusion

The Sheer Mass of Customer Data, Spread Across Various Systems, Makes It Impossible in Sales Management to Keep Track of Everything. CRM systems, Excel and BI tools provide nice sales reports, but slow down sales in terms of negotiation and in their view of the future.

Prescriptive analytics and automated AI-based analyses help companies provide their teams with information about risks and potential. In this way, all data is actually used and transformed into sales campaigns. This saves sales teams time for analyses and allows them to take care of their customers more efficiently.