Franchise case study: LeadGenius has helped many clients target small businesses such as hotels, restaurants, gas stations or cafes globally.

The Challenge

A LeadGenius client came to the table with a dirty database challenge… after years of buying contact, intent, and intelligence data from bulk data providers who failed to help them implement and use the data correctly AND then having their sales reps updating (or not updating) and adding notes to each contact record, they had a CRM that was almost unusable and most certainly untrustworthy.

The LeadGenius client targets what seemed like small businesses – hotels, restaurants, gas stations, etc., but after taking a closer look with LeadGenius, they realized most of these small businesses are franchises. And those franchisees owned anywhere between a single franchise and nearly 30 franchise businesses.

But they had NO data about who these franchisees were. They couldn’t entity map back to the franchise owner. This created problems with forecasting and prospecting into accounts.

• According to their CRM, there might be 6,000 separate locations in a given territory and they would forecast hiring and revenue based on this but, after working with LeadGenius, they learned that there were only about 800 franchisee owners who actually owned all of these various locations — meaning there were 800 opportunities, not 6,000.
• Their teams had no way of prioritizing prospects because they didn’t know if it would be a single location sale or a multi-location sale until deep into the process.
• Because they didn’t know anything about these franchisee owners, as big data providers don’t have this information, the sales and marketing teams wasted time prospecting the wrong people at a location.

The Solution

LeadGenius identified who the franchisee owners were – prioritizing by territories they already actively had sales teams in. While they already had some of this data, our LeadGenius project managers and researchers went out and manually did the work of uncovering who these people and holding companies were and gathered accurate, custom contact information.

By having custom entity mapping, the organization was able to understand how many opportunities existed in any given territory, how to prioritize based on the number of locations a single operator managed, and who the actual gatekeepers were. The company saw an immediate uplift in pipeline and an increase in opportunities created. The sales and marketing team were now confident in pulling reports, forecasting the future, and had a full understanding of the best potential revenue opportunities.

Custom Data Points

• Franchisee owner and decision makers
• Legal name, D.B.A. and franchise type
• Number of locations under ownership
• Direct contact phone number
• Franchisee corporate and personal email addresses
• Other related entities