B2B Recommendation Analysis for Cross Selling

Product recommendation engines for B2C e-commerce are widely available. But what if you sell B2B through relationships? The same analysis that the largest retailers use can help empower your sales to team sell more products. 

Recommendation Engine with Apriori

B2B sales executives know that growing an existing customer is easier than finding a new customer. Sales executives that have a plethora of products to sell are not able to focus. A common challenge for them is knowing what product that customer would benefit from next. 

In the B2B setting, a recommendation engine for a B2B salesperson is a powerful tool for focus and to help the salesperson understand similarities between customers.

The Solution

To build this solution, we pull operational data regarding products and sales data (typically from CRM) into a data set for a client profile. This descriptive analysis in itself drives value for our customers. Marketing is often asking for a data-driven customer profile and this is a great side bonus of these efforts. Many of our clients are worried about the quality of their data. Anytime we are working with CRM data we plan for a little extra data cleansing time. 

Once the dataset is cleaned and prepped, we utilize the apriori algorithm to find correlations between products purchased in groupings. This gives us the additional product recommendations for the actual customers based on what products they have to date.

An interesting twist on this use case for this type of association analysis is to incorporate product margin into the effort. For instance: As a salesperson, if I give a low cost/low margin away for free, is a customer more likely to then buy an associated high margin product? As you can tell, there are many interesting options here.

 

The Results

If your sales team spends most of their time in their Salesforce, deploying this model as an API that Salesforce (or your CRM of choice) uses is an easy experience for your sales team. When they pull up their client record, they see a list of the likely cross-sell opportunities based on client products purchased to date.

The results and benefits for B2B recommendation engines are vast.  Increased revenue, increased productivity from sales teams, increased profit, and better customer service are the highlightable results. 

Are you interested in price-volume forecasting with data science at your organization? Set up a 30-minute free consultation with one of our AI experts HERE.