If you have ever been frustrated with the forecasting process and accuracy at your company - this episode is for you!

Guy Rubin is the founder and CEO of ebsta, a leading provider of Revenue Intelligence - the next generation of forecast management.

Guy founded ebsta to automate the logging of sales rep activity directly into their Customer Relationship Management (CRM) like Salesforce and Hubspot. Over 50,000 companies have used ebsta in this environment which is when the breakthrough happened to begin scoring target buyer relationships - essentially a "relationship score".

The strength of relationships is a key factor in an opportunity's probability to convert into a new customer....and thus making the revenue forecast more accurate. More on that later in the episode.

Back to the core problem, ebsta has been solving for years - having timely and accurate account, contact, and opportunity data in their CRM. Since most of this data is captured in their email, and/or calendar. By using technology to capture every email, event, and meeting with an account or opportunity, it can be automatically imported into the CRM. Then, a company can use AI to determine the frequency of communications with an opportunity and begin to create an "opportunity score" based on the recency, frequency, and level of activities with specific opportunities.

What about including insights from "conversational intelligence" platforms? This is another signal that ebsta uses to evolve the "engagement score", but Guy highlighted that CI is only one signal that informs their platform.

Intent data is another signal that ebsta uses to inform and evolve their engagement and thus opportunity score. In a recent research report that ebsta published, one of the challenges is to determine what is the actual impact of intent data on the opportunity "win rate". In this report, ebsta was able to identify the level of influence that intent data has on win rates.

Forecast accuracy is a challenge for every company. Initially, Guy felt the "ebsta" internal forecasts were superior to those of a "bottoms-up" process that begins with the AE or front-line sales manager. Those customers still require the ability to include the sales "bottoms-up" forecast, the ebsta automated forecast is typically within a +/- 5% error of margin - which is superior to the 69% of companies that miss the forecast by +/- 10% or greater.

If you are involved in your company's "forecasting process" this conversation with Guy provides great insights and ideas to enhance your forecast accuracy!!!