“We have a better understanding of who we’re selling to today and which companies are more likely to buy from us. With Mintigo, we’ve gained a lot of efficiency.”
– Cameron Conway, Director of Customer Insights at Red Hat
Red Hat’s main goal in working with Mintigo was to increase its marketing contribution to the sales pipeline and improve overall customer acquisition rates by more than 15%. The company plans to increase top-of-the-funnel new leads by 25% and increase the conversion rate from inbound inquiry to qualified lead to 15%. To achieve this, Red Hat plans to provide more relevant and personalized content and product offers in order to increase conversion rates.
Red Hat provides enterprise-strength, mission critical software and services in today’s most important IT areas: operating systems, storage, middleware, virtualization, and cloud computing. Red Hat’s open source model supplies enterprise computing solutions that reduce costs, and improve performance, reliability, and security.
Red Hat needed more robust data on leads and prospects to identify those who are most likely to purchase one of its solutions. Better data will enable better segmentation, highly targeted campaigns, and nurture tracks as well as identify cross-sell and upsell opportunities. In addition, continuously updated robust data from the web will allow identifying buyer personas and highly likely buyers.
Mintigo’s Predictive Lead Scoring and Data Enrichment application was implemented at Red Hat directly into Eloqua through the Oracle Marketing AppCloud. This enabled Red Hat to predictively score as well as enrich contacts with relevant data provided by Mintigo in real time.
With Mintigo, Red Hat was able to quickly build predictive models for each of their product lines and identify the CustomerDNA™, or the data driven ideal customer profile. Mintigo’s platform used customer data provided by Red Hat as well as 2,000 continuously updated, unique data points from Mintigo on over 10 million companies and 100 million contacts in the US.
Once the models were created, Mintigo was able to enrich each contact in Eloqua with:
- Marketing Indicators (MIs): In Red Hat’s case, the company wanted to enrich its database with marketing indicators such as “Uses Hadoop,” “Has Enterprise Architects in the Company,” and “Uses WordPress for Company Website.” Marketing indicators are data points from the web that Mintigo tracks and that were identified by the predictive models to show high correlation with purchase. Mintigo’s Predictive Lead Scoring & Data Enrichment App for Eloqua then enriches every lead with these data points.
- Contact information: data points such as job title and address as well as firmographic data such as industry and company size.
- Predictive scores: to determine how closely matched the contact is to the ideal customer profile generated by the predictive models of Mintigo for every product.
Based on the analysis from the predictive models in Mintigo, Red Hat was able to identify that 20% of all of their contacts in Eloqua are similar to more than 83% of customers that purchased one of their solutions, and 20% are similar to 80% of the customers for another offering. This means that the marketing and sales reps now know which contacts to focus greater resources on or put into a high-touch nurture path versus routing to a lower resource path or a more efficient drip campaign.
For example, Mintigo was able to identify a group of potential customers for Red Hat’s virtualization product from understanding the CustomerDNA™; this group was different from the group that Red Hat was originally targeting using basic demographic segmentation from existing data that they captured in Eloqua.
In another example, Mintigo was able to identify the segment of Hadoop users in their Eloqua system so that they can offer more relevant content around open-source technology that Hadoop users would find interesting. Identifying open-source users is a difficult task, as it involves the gathering of external data that most companies lack.
In addition, every newly generated inbound lead is automatically scored in real time to see which product the lead will most likely purchase, enriched with the additional data that Mintigo provides, and routed to the right programs and people for followup.
Red Hat plans to utilize more of Mintigo’s data in order to define better campaigns and reach additional segments for other product lines. For example, Red Hat wants to better understand how to cross-sell their Middleware product line. Red Hat plans to create new, more personalized campaigns based on the data that Mintigo provides.