How Marketing Can Regain Sales Trust and Impact Revenue with a Better Lead & Account Scoring Model
A few months ago I was on an expert panel put together by the fantastic team at CEB on ‘Precision Lead Targeting and Nurturing’ where the moderator presented the not so shockingly stat on how likely sales is to trust leads referred by marketing demand generation program. As you can see below, sales reps hold marketing leads in low esteem - even below those involving procurement:
According to SiriusDecisions, 68 percent of B2B companies have some form of lead scoring, but only 40 percent of salespeople get value from it! Why? The lead scoring methods that have become so popular in SaaS organizations around the globe are intrinsically flawed.
What Got You Here, Won't Get You There
Traditional lead scoring takes into account a variety of predetermined factors that help in qualifying a leads propensity to purchase. Savvy businesses will likely have established scoring criteria that includes a combination of demographic attributes, lead source and estimated budget.
Popular marketing automation tools such as Marketo and Hubspot, may also complement this data with what they call “behavioral attributes,” which by their definition includes online activity such as page views, email engagement or content downloads.
So, what’s wrong with this strategy? The “behavioral attributes” used by traditional lead scoring models are focused on the top of the funnel. But, today’s B2B buyer journey is more complex, non-linear and circular than ever before.
Traditional lead scoring is failing because:
- It’s based on assumptions
Setting up lead scoring in a marketing automation tool requires a slew of guesses and assumptions on what attributes indicate a lead is positively or negatively inclined to make a purchase. Even those that tout “predictive lead scoring,” look only at factors such as “information filled out on your website, social information, demographics or media written by your company.”
Yet, there is no evidence that any of these factors contribute to a lead converting for your specific organization. Every company, product and customer is different. A one-size-fits-all model will ignore the criteria that make your organization unique. In fact, even Hubspot’s explanation of their lead scoring model states, “nailing down a consistent formula for this can be really difficult for many marketers, and often comes down to a “try and check” process.” But, who has the time to continually “try and check” for lead scoring accuracy?
Modern marketers must be data-driven to eliminate room for error. A successful lead scoring system will not force you to guess, but instead, provide true indicators for the scoring attributes that directly relate to your company.
- It’s labor intensive and stagnant
If you’ve taken the time to read the 56 pages Marketo document on lead scoring, my guess is that you’ve invested an incredible amount of energy into building out a lead scoring model. While this formula may seem accurate now, will it still be accurate in three months?
There is nothing stagnant about the way buyers engage with your brand. New channels and metrics influencing the buyer journey are introduced every day. Committing to a lead scoring model that doesn’t dynamically adjust as your buyers do, will produce inaccuracies. And, without manually adjusting on a regular basis, miscalculations won’t be addressed in a timely manner.
- It does not include product engagement data
If your company offers a free trial, operates on a freemium model or upsells based on product usage, it’s imperative to monitor product engagement at a granular level. A true behavioral lead scoring model will identify what features were used, how often they were used, track other users from the same organization and identify when a heavily engaged user is ready to upgrade.
According to Tomasz Tunguz, when a sales team calls leads that include product engagement data, buyer typically convert at 25 to 30 percent! However, in traditional lead scoring systems, product usage is completely dismissed. Companies rely so much on who the person is, rather than what they’re doing.
- Account-based is changing everything
Just when you thought you have arrived at lead scoring nirvana, came Account-Based Marketing and changed everything; now instead of scoring individual leads you need to score entire accounts, but traditional CRM & Marketing Automation systems where never built to handle accounts... Without account scoring (as well as Leads to Account Matching which is table stakes in today’s ABM world), your inside sales rep can be qualifying John, your marketing team can be emailing Jennifer and your outside sales rep can be showing demos to Kevin, all without knowing that they all belong to the same company...This creates confusion not only for your buyers that may find themselves in different sales cycles, but also for your marketing team that is wasting resources and could potentially delay or lose the sales opportunity.
For lead or account scoring technology to provide value, it has to be smarter. According to Gartner, 70 percent of leads are lost from poor follow-up. But, with hundreds of leads coming in every day, how do you prioritize? Organization’s need a full-time, intelligent system for monitoring successes and failures. One that automatically adjusts the scoring based on real-time data and results.
Predictive marketing vendors have tried to solve this problem and failed since their scoring model is still relying solely on top of the funnel data, ignoring the modern buyer’s circular, non-linear journey.
Fit + Intent + Engagement - A Better Scoring Model
At CaliberMind, we’ve tackled this problem through the consolidation of data, the integration of essential applications and dynamic lead and account scoring functionality. The platform integrates fit, intent and engagement data from multiple internal and external data sources, your marketing automation tools, CRM, support, chat, web and product. A lead or account score is assigned that dynamically changes based on product engagement, firmographic, demographic and behavioral criteria. Automated triggers then push this data to feed Salesforce, your marketing automation tools and more.
We’ve put this approach to work with our customers who are reporting increase in qualified net-new leads, MQL to SQL conversion, and pipeline acceleration. They use the scoring model as a single source of truth to:
- Build Total Addressable Market
Know whether there are 10,000 accounts or 1,000 you can really go after and insure that marketing and sales only work on high-fit accounts.
- Target Account Selection
Go beyond basic data about companies to more intelligently, and easily, select your target accounts beyond the strategic accounts your sales team already is working on.
- Provide Sales Team with Buyer Intelligence
Give your sales team data-driven triggers at the account-level to take the right actions and personalize outbound campaigns.
- Dynamically Target Accounts
Dynamically target accounts based on data and trigger the right actions in your sales development and sales teams.
- Personalize Campaigns
Automatically trigger account-based advertising with intent signals and engagement data. Thanks to our increasing number of partner integrations, you can run multi-channel account-based marketing campaigns with consistent messaging.
I’ve decided to share the scoring model here in hope that it would help marketers regain sales trust and impact revenue. Ready? Lets Go!
Not All Lead/ Account Scoring Data is Created Equal
Lead qualification and scoring is a data problem not a marketing problem. It’s about spotting Fit + Intent + Engagement. But how do you find it? The answers to ‘Fit’, ‘Intent’ and ‘Engagement’ are outside your marketing tools. You need to fill in the blanks from elsewhere to have all the data to personalize messages and enable sales. You need to capture this data from multiple different places, and connect it to your key marketing tools.Let's start by classifying the types of data we want to work with since not all scoring data is created equal.
Refers to leads and accounts that fit the Ideal Customer Profile of who your company is trying to market and sell to. Preferably, fit refers to your ICP + AI-assisted scoring. Think of ICP as the firmographic, technographic, geographic, etc. filters you apply to your data to narrow your accounts to your target market, plus an incredibly powerful machine that considers thousands of variables to see if those accounts are similar to your healthy customers, open opportunities, or whatever you decide is best for your business to build your model from.
Intent data shows what people at companies are searching for and consuming on the internet (not just your website). This is a signal of possible “intent” based on their current interests relative to historical data. Intent data can be from first party (your web properties) such as: anonymous website visitors, forms etc’ or third party web properties such as keywords searches and industry publications (aggregated by vendors such as Bombora), online review sites (G2 Crowd, Capterra), niche publications, public forums etc’ (we use a proprietary CaliberMind’s crawler to scan and index those). At CaliberMind we assign different score based on the level of intent - Low, Medium, High.
Engagement aggregates activity from all the people who are interacting with your company at the account level so you can understand and act on this response and behavior. Ideally, you want to focus on high-value activity. For example, we prioritize companies that spend time on our product pages more than those that visit high-level blog posts because it’s a better signal, of course, of who may be evaluating our product. Having the ability to track people who are not in your database (and are therefore anonymous) is an important capability.
In my next post I’ll describe how to use a marketing intelligence system to ingest all the data, attribute and take action on it to alert your sales team, create smart lists and nurture campaigns in your marketing automation and target your key accounts with display and social advertising. Stay tuned!
The Intelligent Marketer
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