Analyze This: Why Predictive Sales Intelligence Boosts Sales Results

Why did Sequoia Capital – the renowned venture capital firm behind LinkedIn and Google – make a major investment in Lattice Engines, the front-runner in predictive sales-intelligence software? What is predictive sales intelligence, and why did Lattice Engines raise capital from Sequoia?

Shashi Upadhyay, CEO of Lattice Engines, told me in a phone conversation to think about the advances in analytics that such B2C companies as Amazon or Netflix pioneered by offering nuanced recommendations. For example, if you have purchased books about French wines on Amazon, you may get recommendations about French cookbooks or travel books about Burgundy. How does Amazon find out which books might interest you? They compare the shopping history data of other customers and find out which patterns resemble yours.

Lattice Engines is now applying the power of data and predictive analytics – a staple in the B2C world – to boost B2B sales and marketing productivity. The insight is that the explosive growth of data about companies and purchasing decision makers contains hidden but invaluable intelligence for frontline sales teams. Lattice Engines has encapsulated this vision into its sales intelligence software, salesPRISM.  Shashi explained that this is the first solution that combines a company’s internal view of its customers and prospects (e.g., purchase histories, product usage data, customer service records) with external information about these accounts and decision makers (e.g., news sources, company Websites, social media).

What’s really unique about this? It’s not about overloading reps with even more data. It’s about transforming enormous amounts of data into intuitive, simple, ongoing, account-specific recommendations for when and how to engage with each account.

Shashi, who holds a PhD in physics from Cornell University and was a partner at McKinsey before starting Lattice Engines, explained that when it comes to running a sales organization, data-driven decisions yield significantly better and measurable sales outcomes compared to the traditional, gut-feel approach.  He noted that salesPRISM is being used by thousands of reps at leading sales organizations, including ADP, Dell, and VMware, which have experienced double-digit sales productivity gains within the first year of deploying the software.

Shashi emphasized that predictive sales intelligence is not the same as backward-looking reporting. In today’s battle for improving sales, a business needs to move from looking into the rearview mirror to looking through the windshield and predicting what’s next. The big bet is that the mix of internal and external data, smart math, and a continuous flow of new, predictive, account-level insights will make reps more effective.

While data and analytics in sales have always been seen as an auxiliary to a main function (like a PowerPoint presentation to a speaker), Lattice Engines sees analytics move into the hub of a sales and marketing organization, informing every customer interaction.

The Impact of Analytics

Independent research by CSO Insights shows that when companies arm their managers with better, new information through analytics, they enjoy better results:

15% higher close rates of forecast opportunities
20% more reps meeting or exceeding quota
34% lower sales-rep turnover

Traditional analytics solutions, such as Birst, Cloud9, Right90, and SAP BusinessObjects, offer improvement in five areas:

1. Ability to better view the sales pipeline
2. Ability to measure and track sales performance
3. Ability to create more accurate sales forecasts
4. Ability to visualize performance
5. Ability to track competition

Lattice Engines goes a step further by suggesting to salespeople where future sales opportunities lie based on a rich set of internal and external data. The Intelligent Targeting module within salesPRISM enables each rep to easily identify the most promising targets (who is most likely to buy what and why?) and deliver the best content suggestions to salespeople so that they can have more relevant and productive conversations with customers.  The key to turning the recommendation into a sale is, according to Shashi, the ability to empower the salesperson with everything he or she needs to know to have the most productive conversation. That means no boilerplate pitch, but an effective conversation around business issues, effective solutions, and profitable outcomes. The ability to create dynamic, on-the-fly, needs-based talking points is called Contextual Conversations within salesPRISM.

Andrew Somosi, SVP of marketing and business development, said that when it comes to making decisions in account targeting and injecting intelligence into business conversations, there are three horizons: the salesperson’s view within his or her territory, the company’s view across all customers, and the whole market view. The trouble with relying on just our individual knowledge is that we see only what we know. With sales intelligence software,  we have the opportunity to tap into the universe of insight around us. The role of sales intelligence software is to enlighten both buyer and seller to a higher level of insight, which leads to better business decisions and happier customers.

Vital Stats:
Lattice Engines was started in 2006.

Total capital raised before this round: $1.5 million
Number of customers: 20+ Fortune 1000 companies
Integrated with salesforce.com, Oracle, Microsoft Dynamics, Custom CRM
Number of full-time employees: 70
Key industries: High tech, business services, asset management, commercial banking
Key customers: ADP, Dell, VMware

 

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Comments

[christian louboutin]

This was an interesting problem. As you may know, SharePoint 2010 allows you to create a central hub of content type and publish, or syndicate those content types to multiple sites or even cross farm.

[coat stand]

Independent research by CSO Insights shows that when companies arm their managers with better, new information through analytics, they enjoy better results:

15% higher close rates of forecast opportunities

[Vorsight]

Are there any examples of much smaller companies around $5-10m who are utilizing LatticeEngines? What sorts of measurable results have they achieved? Vorsight is only about $4m revenue, so curious to see what other similar firms are doing around predictive analytics.