Don’t Just Score Leads: How Mindjet and Juniper Are Predicting Their Next Customer #EE13
Yesterday, Brian Kardon was joined by Juniper Networks’ director of enterprise marketing, Abner Germanow and Mindjet’s CMO, Jascha Kaykas-Wolff to discuss the shift towards predictive marketing, specifically how predictive analytics can be utilized to inform better lead scoring at Eloqua Experience.
Brian kicked off the panel with the shift in marketing. Marketing has been moving from being viewed as an art form to being viewed as a science. Technology is changing our lives as consumers and professionals in business. We are shifting from radio to Pandora, Blockbuster to Netflix, taxis to Uber, a physical bookstore to Amazon. We are adopting content marketing, marketing automation, lead scoring, etc. And what are the results? According to SiriusDecisions, 94 percent of marketing qualified leads will never close. What’s more, over half of sales reps in the US missed their quota last year (CSO Insights).
How can we, as marketers, harness the learning from our consumer counterpoints like Amazon to develop smarter, more predictive marketing?
Amazon knows more about you than just the products you buy. It tracks what you covet, what your neighbors and friends buy, and can identify if you are cheating on your partner based on your activities, behaviors, etc. Data science is playing a major role in the success of Amazon. 35 percent of Amazon’s business is stemming from product recommendations based on data science. Through predictive analytics, Amazon is changing its business.
Traditional lead scoring just scratches the surface of the data that is available to marketers – in fact only five percent. Like an iceberg, marketers can only see a small portion of data available within CRM and Marketing Automation. It’s what’s below the surface that is most predictive and informative. Underneath the surface, there’s information from job postings, government contracts, government grants, VC funding, litigation, patents, credit ratings, product usage, financial history, deployed technologies, purchase history and more. These attributes are discoverable and can help companies predict their next customer. Next, Brian invited Abner up to discuss Juniper’s successes.
Abner Germanow was up next to share Juniper’s story around big data and predictive analytics. Juniper does business with large scale, global corporations and is a multi-billion dollar company. With 9000 employees spread across 124 offices, there is a lot of tribal knowledge trapped within different business units. The question that Juniper is looking to answer: How can we balance tribal knowledge with the available data on our customers and prospects?
Like many companies, Juniper has a complex sales organization. To describe this, Abner focused on the tale of two reps. He first described the ‘George Clooney’ rep. He has one account and knows more about that company than its own employees. He is the rock star who masters that account. Juniper also has a group of commercial reps. These sales reps have 1200 accounts and know fewer contacts and organizations. It is easy for them to get lost in research and waste time talking to the wrong prospects.
Next Abner walked the crowd through the tale of two leads.
For one lead, we know that it watched a webinar and read a whitepaper. But for the second lead, we know that it also happens to be in the financial services industry, has a huge install base and has recently completed a move to a new office. All of this external data is incredibly telling of a company that is ready to buy Juniper’s products, especially for the reps who are managing 1200 accounts.
Results: Juniper has seen tremendous lifts in opportunity value, seeing as much as an 82% bump in pipeline when reps researched an account within Lattice. One sales rep even said, “It gives us the information we need so we don’t look dumb.”
Jascha Kaykas-Wolff next shared his experience in using predictive analytics to solve Mindjet’s curse of abundance – the flurry of inbound leads from free trial requests. Mindjet releases, on average, 20 new opportunities to the sales team every day, but the sales team isn’t able to actively engage all of the leads. There are simply too many opportunities to target.
Jascha has always been on the cutting edge of marketing technology. As an early adopter of Eloqua for Marketing Automation, Jascha is now running multiple nurture campaigns, focusing on scaling the database and operating a sophisticated marketing stack including Jaspersoft, Lytics, Tealium, salesforce.com, Webtrends, Lattice, Marin Software, Optimize and more.
Mindjet is tracking thousands of records that are changing hourly to gather explicit data and combining that with implicit data from the Web and social media via Predictive Lead Scoring to identify the leads with the highest likelihood of purchase. With Lattice, Mindjet assessed 300 variables to uncover the right mix of predictive attributes to identify the best leads for sales to engage. Some attributes that were proven to be predictive for Mindjet include: employee-to-site ratio, social index, hiring trends, usage of cloud applications, number of locations and growth index.
Results: The results to date for Mindjet are huge. The company is seeing a 4.4x improvement in conversion to SQLs for the highest rated leads. As Mindjet looks ahead to continue to optimize predictive marketing, the company will roll the program out internationally, incorporate additional data sources and apply learning to scripts and product marketing.
The era of big data and predictive analytics is now. There is more information to discover about a prospect than ever before. Leading marketing organizations are embracing predictive analytics and data science to drastically improve their performance.