How Sales Intelligence Helps You Close More Deals
June 3, 2020
What Is Sales Intelligence, Anyway?
Once upon a time, sales prospecting was mostly art and very little science. Reps would research prospects and work their way through lead lists in a largely hit-or-miss fashion. With the rise of digital marketing, everything changed. Sales teams had more leads and data than ever to deal with, and less time to do it. They needed new ways to rapidly cut through the noise, find the real opportunities, harness the best insights and move sales conversations forward at a faster clip.
That’s why leading organizations have embraced sales intelligence practices and tools, helping them zero in on the most promising prospects, identify the most relevant sales triggers and apply the most effective selling strategies.
Sales intelligence is the collection and analysis of data on prospects, customers, competitors, and the market environment. That can include information about a prospect’s job, needs and pain points and where they are in their consideration process. It can also cover competitors’ offers, market trends, company information and other data that might be useful in targeting, understanding and engaging prospects. If the information exists in any form, it can be aggregated by a sales intelligence tool and served up to your team.
How Sales Intelligence Helps You Close Deals
First and foremost, sales intelligence focuses and refines your research. Sales technology collects and aggregates data from a wide range of public and private sources including demographic and firmographic databases, websites, news services, social media, independent research and more. For companies that sell B2B, this kind of intelligence is a must for demonstrating to prospects that the reps understand them and the environment in which they work. From third-party B2B data, reps can get a picture of company decision-makers and influencers with organization charts, LinkedIn profiles and actions such as whitepaper downloads. Combining that knowledge with deep industry insight helps sales teams prioritize and focus sales rep time and energy throughout the sales cycle.
Sales intelligence practices and tools are used across the pipeline. Here are some common use cases:
- Lead generation: In order to focus lead generation on likely prospects, sales tools are put to work identifying ideal accounts and understanding what makes them buy so lead gen teams can improve their processes and results. Example: Mapping prospects to various stages of the buyer’s journey will help you improve marketing campaigns with more targeted offers.
- Lead database enrichment: Data is gathered and appended to prospect and customer records to develop a fuller picture of who the decision-makers are and what they want. Example: An organization chart matched with a prospect record can show who is interested in the offer and who is likely to sign off on the purchase.
- Lead qualification and scoring: This is the process of screening prospects before sending them to sales reps for further action. Example: Data on prospect actions and attributes that may mark them as a likely buyer.
- Compiling lead activity: With the frenetic pace of digital engagement, it’s easy for sales teams to lose sight of the activities that matter to a sale. Sales intelligence tools can help identify and surface the most important lead activity data to guide better decision-making.
Example: Prospects who visit pricing web pages are flagged as more likely buyers than those casually poking around a blog (though we appreciate you too!).
- Research on industries, companies, markets, opportunities and individuals, daylighting the company’s purpose, leadership information, financial and technical signals and recent news developments can all help reps understand what’s going on at the company and find angles to engage. Example: Knowing that a company is seeking funding is a likely indicator it’s in a growth phase. If your company sells products or services that support growth, it makes them a better target. If your offer helps companies mature or downsize, you should look for other signals.
- Tracking, understanding and curating the signals that indicate readiness to buy: Of all the engagement actions to track, proven buying signals are the most meaningful. Example: Activities like asking about pricing and modes of payment are good signals that a prospect is close to a sale.
- Gathering contextual data from social media or news sources. Monitoring prospects’ social media feeds can tip you off to opportunities you might otherwise miss. Example: a prospect might mention planned expansions, initiatives or organizational changes that signal a need for your product.
Where Sales Intelligence Tools Go Wrong
It’s great to have all this data. But it’s not enough. You need a way to sift through it, understand it and figure out what it means for your sales efforts. What does it mean, for example, that the company you’re going after is in its third funding round in five years and that the IT manager downloaded your white paper? Possibly nothing, possibly everything. It all depends on the relationship of these signals to each other, to the buying process and to your offer – and what your sales team can do to help them along.
You need to support sales reps by giving them a systematic and effective way to make good decisions quickly. By itself, more data doesn’t help your team close more deals. For that, you need tools and practices that guide sales reps to the right leads and help them prioritize.
The explosion of new sales intel tools has radically increased the amount of information sales teams have access to. It’s not uncommon for integrated tools to have dozens – even hundreds – of individual pieces of information about a prospect’s demographics, behavior, assumed motivations, purchase history and more. More information might seem like a good thing, but it’s often too much, leaving sales reps drowning in a sea of possibilities. Reps don’t have time for that. Instead they need a manageable amount of informant they can use.
By the same token, reps can’t be expected to open ten different tools to learn about the prospect before they pick up the phone, nor should they have to manually share and collate lead information, competitive research and industry news.
To put it simply, most tools generate a lot of noise, which can waste a huge amount of your sales team’s time and hurt their ability to make quota. The following all-too-common scenario illustrates the problem:
A sales rep uses a lead list tool to sort and search prospects. The tool doesn’t automatically surface the most qualified leads, so the rep attempts to cull the list, using firmographic information and guesswork, thinking at least they can rule out the organizations, opportunities or stakeholders unlikely to buy their product. It takes a lot of time to winnow the list, without a lot of confidence in the results.
Next, the rep runs the list through a sales qualification process, but the process is too general and it doesn’t provide enough detail about where the prospects are in their journey. It’s impossible to tell which ones need more nurturing and which ones are really in a position to purchase.
Without direction on where to focus, reps just start calling leads on the list. Inevitably, reps spend hours working on prospects that will never convert. They start to wonder if they should have even bothered with the whole prioritization and qualification effort. By the time they do (accidentally) come across a hot lead, they’re exhausted and not pitching at their best level. They lose the sale.
This story shows how, despite all the rich information surfaced and compiled by sales intelligence platforms, reps can still go off the rails without clear direction. Even with great sales enablement practices and tools that speed up the process of gathering and aggregating data, sales reps are left doing what they’ve always done: tedious research, cold calling, sending endless emails and working leads that go nowhere.
What Is Sales AI?
Sales teams need tools that are smart enough to help reps make sense of data, and then act on it. This is where sales AI comes in. Not even the most talented salesperson could possibly make sense of the multitude of signals that prospects generate, let alone figure out how the thousands of data points relate to each other. What patterns indicate a propensity to buy? Humans can’t do the math. But AI can.
That’s what Infer’s predictive lead scoring is all about. It uses AI to analyze and understand the relationship among thousands of data points, discovering patterns that signal a readiness to buy. Specifically, Infer pulls the data from your CRM and your marketing automation system (MAP) and combines it with Infer’s own huge database of company information. It combs through the aggregated data, looking for patterns that signal buying propensity and a good fit for your products. Crucially, the algorithms it uses are hand-tuned for your company by a dedicated data scientist, then tested for accuracy.
Infer uses the customized algorithms to build exacting behavioral and fit models, which in turn are used to score prospects. Infer then serves up the scores in an actionable sales roadmap that dramatically speeds up your sales team.
Rather than spend months on the traditional hit-and-miss process of finding out which leads are good, Infer’s predictive lead scoring shows reps what they need from the outset: a list of who to call now, who to email this afternoon, to nurture more, and who to drop. All of this guidance is displayed right in their CRM.
Infer is constantly testing and refining its model to make sure it still holds. Infer sets aside 40 percent of the available customer data outside its model. Once the model is constructed, it measures its predictions against real buyer behavior to make sure its model stacks up.
Now that reps know exactly which leads to focus on, they can make much better use of the intelligence provided by other tools. They can toss out the bad leads and focus on the ones with a high probability of closing, leading to higher win rates, more deals and sales acceleration. App-tracking company New Relic improved conversion by a factor of 9.6 with Infer, which helped the company land the SirusDecisions 2016 Demand Program of the Year award.
See how Infer can transform your sales performance by helping your reps cut to the chase. Get a demo today.
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