Updated on November 22, 2018
Of the innumerable applications of artificial intelligence (AI) in the B2B technology space, the one I'm paying the most attention to is sales tech. I'm particularly excited about this application because it meets the criteria needs for AI to be successfully applied. These are:
- A wealth of data. Companies like Datafox, Clearbit, FullContact, and Toofr are supplying company and contact data to thousands of companies. The availability of data is critical because AI needs to be trained, and the input is lots and lots of structured data.
- A hungry userbase. Sales reps are always looking to get a competitive advantage on their competition -- both inside and outside their sales teams. This means they're willing to try new tools that save them time. Most of the AI applications to sales involve cutting out research steps, effectively increasing the productivity of sales reps. Case study: Nudge, an email writing assistant that finds interesting things to mention in your emails to prospects.
- Capital for research. Finally, companies and financial institutions need incentive to invest in this technology. Every company has a sales need of some sort, and as they grow and begin selling to other companies, they'll eventually need to hire a sales team. Facebook began as a consumer product, but it makes all of its money by selling ads to businesses. To do that it has a huge sales team.
The various categories of sales AI that I've seen are:
- Inference on who your best customers are
- Predicting which of your cold or new prospects will close
- Finding points of common interest between reps and cold prospects
- Analyzing sales rep performance to better predict quota
- Training sales reps to make better calls
Each of these categories make sales reps more productive and efficient. Since you’re likely to fire one in three of your sales reps, that’s a huge savings potential.