Case Study

BACKGROUNDConnectWise is a business management software company that has grown significantly in the past ten years.

CHALLENGEPrior to using Mintigo, ConnectWise didn’t have an effective way of prioritizing leads by likelihood to convert, forcing Sales follow-up activities to be more reactive rather than proactive, with the Sales team chasing every lead. Without a system for prioritizing leads, ConnectWise relied on gut instinct rather than data and needed a tool to optimize their efforts. SOLUTIONConnectWise used MintigoAI to build a lead-based, multi-product model to score inbound leads as they enter the system. ConnectWise was able to build its model using thousands of data points collected on millions of companies globally. The Mintigo team matched ConnectWise’s data to Mintigo’s database of over 25 million companies and 200 million plus contacts and appended the records with 4,500 fit indicators and over 1,000 intent-based behavioral indicators. Mintigo gathers this information by monitoring the online behavior of several million B2B companies and tens-of-millions of prospects and decision-makers. Mintigo’s indicators include information on financials, staff, hiring, technologies, and the marketing and sales tactics of each company’s digital footprint.

This data was used as the foundation of ConnectWise’s predictive model. Using MintigoAI, ConnectWise was able to analyze this digital footprint and, with the help of machine learning, predict a lead’s likelihood to convert into a customer.

RESULTS

ConnectWise uses MintigoAI to identify the highest quality leads and to forecast sales pipeline

www.mintigo.com info@mintigo.com

“After seeing the results of the first model, we’re considering hiring more people to leverage MintigoAI. Our sales team has fully bought in and is buzzing about the possibilities.”

- Rick Collins, Senior Marketing Systems Analyst

Mintigo Rank SQL % SQO % Win % of SQO # of Leads to Get 50 SQOsA 27% 23% 23% 217

B 21% 16% 17% 313

C 15% 12% 20% 417

D 11% 9% 11% 556

Mintigo Model Validations

www.mintigo.com info@mintigo.com

ConnectWise built a multiproduct model that automatically assigns each inbound lead three separate scores, each score correlating to the lead’s likelihood to buy a specific product. The model gives the sales team insight into which product is the best fit for each lead. The model has been integrated into Oracle Eloqua, which enables ConnectWise to effortlessly score and enrich leads with fit and intent indicators in real-time as they come in through forms on the website. The validations of the MintigoAI model indicate that A-ranked leads progress down the funnel and successfully convert at a higher rate than all other leads. Using the Mintigo model, ConnectWise can determine the number of leads per rank that it takes to get 50 Sales Qualified Opportunities, effectively forecasting their pipeline. ConnectWise has also been able to identify accounts that are 5x more likely to convert into a closed-won deal. The team is now scoring nearly every form submission using the Mintigo database.

EXPANDING INTO ADDITIONAL USE CASESAfter the outstanding results of the first model, the team wasn’t content to use MintigoAI for inbound lead scoring exclusively. ConnectWise is exploring additional applications of MintigoAI and are even considering hiring additional employees to take advantage of the power and diversity of the platform. The team is in the process of leveraging MintigoAI for the following use cases:

Account-based Marketing• Prospecting within the database – ConnectWise intends to use their resources more effectively by targeting A and

B ranked leads currently in their database. • Discovering net new accounts – The team will generate lists of high-ranking accounts that are not currently in their

database for outbound ABM using Mintigo Demand Center.• Improving sales alignment – The marketing team plans to help close deals faster by feeding sales the 50 top accounts

per region based on predictive account scores.

Cross-selling to existing customers • Identifying the right targets – ConnectWise is in the process of building cross-sell models to identify customers that

are likely to purchase multiple products. • Reaching out at the right time – Intent indicators from MintigoAI will be used to identify and send product information

to customers that are in the market for software similar to their own.

Segmented models for other markets • Creating segment-specific models – ConnectWise built a model to score and prioritize leads in a new segment

they’re focusing on. This segment specific model gives these leads a more accurate score than a general model would.• Expanding segments – The team identified a spike in specific segments that have historically comprised a smaller

percentage of ConnectWise’s audience. ConnectWise plans to expand and improve the segment’s inbound nurture campaigns to capitalize on this influx.

• Leveraging fit and intent indicators – ConnectWise will incorporate Mintigo scores and marketing indicators into the inbound nurture campaigns mentioned above. They will craft compelling messages around their products using information gathered from the indicators regarding a company’s current technology configuration.

ConnectWise Case Study

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