In Unpredictable Times, How Do You Predict Revenue? Hint: You Need to Know Who’s In-Market, as seen on MarTech Series

May 11, 2020 Lisa Sharapata

It is no secret Sales and Marketing are still misaligned when it comes to measuring what matters — and it’s affecting companies’ ability to generate predictable revenue6sense’s research has shown more than 80% of B2B companies fail to exceed revenue goals. While adopting account-based engagement practices can help teams perform better, it did not outright guarantee success. At the center of this challenge is the need for Sales and Marketing to use rich, accurate data to better align their goals and direct their efforts.

Data Drives Predictable Revenue

Account-based engagement relies on your teams understanding of what your prospect accounts want and where they are in the buying journey. Without the right data, teams are left guessing. They use outdated and arbitrary metrics like MQLs and SQLs to define pipeline growth goals — even when these metrics show only a small part of the overall picture.

Only 48% of BDRs consistently hit quota regardless of the work they put in. If BDRs struggle to find consistency, it prevents accurate predictions about revenue and pipeline growth. This affects marketers, too. When sales and marketing are misaligned on prioritized accounts, time and effort are wasted. Marketers aren’t effectively connecting with prospects and warming accounts to get them ready to buy. BDRs then cannot meet and break revenue goals, and the gap between Sales and Marketing widens as frustrations mount.

Sales and Marketing must be aligned on predictable revenue growth as the end result of their efforts. But how can we bridge the gap?

Matching Target Account Lists With Intent Data

To align Sales and Marketing on the goal of predictable revenue growth, your target account list (TAL) plays a key role. Your TAL should represent the best prospects you’re targeting, but many companies are making ad hoc suggestions to fill the list — or either don’t often update their TAL (or even have one at all). Without data to support why a prospect is on the list, marketers cannot deliver personalized experiences to warm the prospect, and BDRs don’t have accurate information to move them down the funnel.

Personalized experiences depend upon accurate intent data from prospects. When companies assess their TALs and plan for predictable revenue, they’re still using lead-level data like MQLs and SQLs to try to personalize outreach. If Sales and Marketing are supposed to be building the pipeline, they need data on intent signals to actually know where the prospect is in the funnel and what they really want.

When data points about intent signals are matched to the accounts in a company’s TAL, it will clarify who is where in the buying journey. Accounts can be warmed more effectively, and teams can better plan toward their shared goal of predictable revenue growth.

Here’s how you can prepare your teams for alignment on building predictable revenue growth:

1. Assess Your Revenue Metrics

Are you still using lead-based metrics like MQLs and SQLs? It’s time to reassess how you’re deploying those arbitrary metrics. Consider account-level metrics like accounts currently engaged, personas engaged per account, deal velocity and accounts in-market. Also, examine your KPIs and goals to ensure they match with those metrics.

2. Realign Sales and Marketing

Bring Sales and Marketing together around your revised set of revenue metrics and goals. Take time to check both teams’ TALs and work toward agreement on why accounts are on the list. Both teams should work toward the goal of predictable revenue growth.

3. Plug Data Gaps

Review your Marketing tech stack for missing data solutions to match account-level metrics and KPIs. Buyer intent data and signals more accurately predict how a prospect moves through the buying journey.

Data solutions should gather third-party data and “dark funnel” data like anonymous visits to your website, and then match that data to your TAL to deploy a more personalized account-based engagement experience.

4. Add AI to Support Scaling Accounts

As your teams start gathering more data over more accounts, you’ll need automation supported by AI to keep generating actionable insights. Those insights include recommendations on what next best actions your teams should take to move a prospect forward. An AI-generated list of actions, delivered in-context with target accounts and their buying stages, uses rich account data to its fullest potential.

When your solutions remove the guesswork from a BDR’s day, they spend more time moving prospects through the pipeline and closing deals. Marketers can then focus on accurately warming prospects with personalized content. Coupled with the right account-level metrics, predictable revenue becomes something more than a pipe dream.

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