If you sit through enough board meetings and are [un]fortunate enough to participate in the budgeting process a sufficient number of times, you’ll learn that there is one department that almost always wins when they ask for more budget — Sales. It makes sense that this is how it works because the Sales team drives revenue, and without revenue there is no business. So when the sales organization indicates that they need additional budget for tools that will help them sell, very rarely do they get rejected. As an investor on the hunt for big markets, after seeing this enough times, I started to take notice.
There is ~$12.8 billion per year spent on sales acceleration technology, which is broadly defined as the tech that sits between marketing automation and CRM. On a per rep basis, that’s $2,280 per year, a number that is expected to grow to $6,790 by 2017. In addition, according to Gartner, CRM is the fastest growing segment in all of enterprise software expanding at a ~20% CAGR between now and 2019 when it’s expected to be worth $43 billion. The business of selling is big.
Given the lack of white space (landscape below) in this sector, I wanted to understand the shortcomings of the current solutions in the market today directly from the sales reps. I spoke to over 20 reps (and managers) across a diverse set of industries. The first thing that I learned is that on average reps use over 7 tools every day as they sell. Since selling is so unique across organizations and verticals, it’s very easy for startups to create new products that have incremental lift for some, and not all. This is a distinctly negative feature in the sales tools market as it breeds “features” in the same way that adtech tends to. After cutting through the clutter, there are three key issues that come up almost across the board; overloading of the lead pipeline, flattening of the sales funnel and neglecting closed customers.
Overloading of the Lead Pipeline
Over the past decade there has been incredible progress in the marketing suite. Companies like Eloqua, Pardot and Marketo have significantly increased the number and quality of leads for sales reps. These prospective customers are not just coming through in larger numbers, they’re also hitting a rep’s CRM with an abundance of new data. Reps today are unable to parse through these troves of information in an actionable way, and have completely thrown out their lead lists and are going back to their old ways of selling.
Flattening of The Sales Funnel
Prospects are now doing deep diligence on products via the wealth of content marketing available today, and also entering the sales funnel through an increasing number of channels. This confluence of factors has wreaked havoc on sales planning and forecasting. Since prospects can learn everything there is to know about a product, integration, and pricing via whitepapers and blog posts, the traditional well-defined sales funnel path from awareness to purchase no longer exists. After coupling this with sales reps notoriously known for not entering information into their CRMs, it has become nearly impossible to forecast the pipeline for sales managers.
Neglecting Closed Customers
The proliferation of SaaS has made it incredibly easy for enterprise customers to adopt new software, but it has also made it easier than ever to churn. Retention, up-sell and cross-sell are now key components of success with almost every enterprise business. Sales reps have historically neglected closed prospects shortly after the deal is done and customer success teams are now scrambling to build systems to address this by creating open communication channels between sales and marketing for up-sell and cross-sell.
While some of these issues are systems and organization specific, there is a suite of predictive intelligence tools that is able to partially address all three. Predictive intelligence means a lot of things, but at the most basic level, these offerings take a combination of big data and machine learning techniques to present previously descriptive information as predictive. For example, instead of telling your reps how many leads they have, it will tell them which leads have the greatest chance of closing if you reach out to them via telephone between the hours of 2–3pm and deliver message XYZ.
The predictive suite falls into three main categories; lead, opportunity, and customer success. You can think of the lead intelligence solutions as helping sales reps allocate their time more efficiently in their outreach. Opportunity intelligence solutions provide pipeline clarity and customer success solutions monitor to predict churn, up-sell and cross-sell. After diligencing these solutions, it’s clear that while most of the vendors in this space claim to do two or three of these jobs, most of them only do one.
Putting aside sales strategy, integrations, and market dynamics (all huge variables), these three predictive pillars differ primarily based upon the sources of the data ingested and the scoring model that makes sense of that data. As you travel down the funnel from lead to customer success, the solutions shift their reliance from external data (Twitter, LinkedIn, 3rd party databases) to internal data (login frequency, seat penetration, tickets). Equally important, the scoring model itself is incredibly unique and decides which variables (or combination thereof) trigger action — this is a not a one size fits all model. When done properly, these solutions are very powerful in their respective categories and can effectively address the three main chokepoints referenced above.
Lead Intelligence
Lead intelligence solutions enrich the profiles of top of funnel prospects and then dynamically rank them for sales reps based on probability to close. By studying the profiles of historically successful customers, predictive lead intelligence solutions are able to then combine data from a number of different sources including the social / open web, proprietary databases and other internal systems (marketing automation, CRM, ERP, etc) saving sales reps the effort of qualifying. If done right, this substantially increases the ROI on sales reps’ time by allowing them to focus less on the top of the funnel and more on what they do best (hopefully, close deals).
Opportunity Intelligence
Opportunity intelligence solutions use a combination of internal data (progress in sales workflow, rate of acceleration in the sales cycle, etc), sales rep performance data, and to a much lesser extent, external data (web). While incredibly useful for sales reps managing opportunities that are entering the funnel at increasingly disparate points, these solutions also provide pipeline clarity to the Chief Revenue Officer. By comparing current opportunities to the historical average closed opportunity, these models can give a probabilistic view as to what deals might close, and also how much they’re worth. This decreases the time that reps are forced to spend on the phone with their CROs for pipeline forecasting, allowing them to focus on closing.
Customer Success
Customer success solutions rely upon the least amount of external data because the health signals of a customer generally come from the inside. These solutions most routinely gather internal data such as product usage, seat penetration across the organization and service requests to predict churn. By cross-pollinating this model with data from lead and opportunity intelligence solutions, predicting up-sell / cross-sell has become a real value driver here as well. When done correctly, these solutions will complement the traditional qualified opportunities that your sales reps are getting from the top of the funnel with a new source of opportunities coming from the bottom of the funnel.
In a space that is seemingly full of features, predictive intelligence solutions are the byproduct of fundamental improvements in technology, and are providing brand new types of value to customers. Even though Lattice Engines, a clear leader in the space, was founded almost a decade ago, there is currently only 1–5% company adoption across predictive intelligence according to Gartner (FWIW, in my informal poll of reps not a single one was familiar with predictive). While it is clear that there are big opportunities in each of these massively underpenetrated categories (we’re interested in investing in all three!), I believe that most of the initial value will be built closest to the revenue source in the lead intelligence bucket.
Predictive lead intelligence solutions are interesting for the same reason that the sales tools space overall is interesting — it’s closest to the money. 34% of reps will miss their quotas in 2015 while sales organizations will suffer from 39% attrition on average (Hubspot). A market that previously suffered from a lack of information on customers is now plagued by an abundance of data at the top of the funnel. As companies start to realize that there has been meaningful progress in the space, they will first focus on the bucket that is closest to the sale, and that’s lead intelligence.
I recently presented on customer relationship management and sales acceleration tools, the deck can be found here.
Michael B. Gilroy
Canaan Partners VC — U.C. Berkeley California Bear — SF Bay Area Native
