Revenue growth is only possible with a solid understanding of our prospects – and no one knows that better than B2B marketers.
When it comes measuring the health of our prospect data, we’re used to showing raw growth in the number of contacts and accounts, or a coverage percentage for target accounts or personas. And we’ve historically used these types of metrics to justify budget requests for investing in more data purchases.
SiriusDecisions, a global B2B research and advisory firm, has historically identified data management proficiency in the following ways:
- Impact: Measures revenue, marketshare, and profit
- Output: Inquiries, proposals, demo requests
- Activity: Emails sent, calls made, requirements written
- Readiness: Database size, SLA completion, skills
These are still great ways of predicting how an organization will perform, especially when entering a new market or rolling out a new product for feature. However, an influx of deeper data offerings has a downstream effect on organizational health that is less understood.
Traditional data health metrics don’t tell the whole story – especially in a world where quality matters a lot more than quantity.
The evolution of prospect data
Contact lists that consist of names, organizations, and phone numbers are still frequent B2B offerings. But limited, inaccurate data is not sufficient to execute an account-based marketing (ABM) plan … or any competitive growth strategy.
The emerging stratification between simple prospect and contact data and account-based intelligence is clearly seen in results and success rates. High-growth companies use 360-degree account-based intelligence to take strategic risks for long-term success; companies who rely on limited, inaccurate, and one-dimensional data spin sales cycles just to keep from losing ground.
What does the new generation of data offerings look like? Account-based sales intelligence includes a lot more than email lists. Sales intelligence provides marketers with company insights (revenue growth, spending budgets, technographics); contact data (verified emails, direct dials, purchase responsibilities, org structure), and buying scoops (planned investments, online research behavior, leadership moves). Emerging sales intelligence like this allows marketers to prioritize prospects and develop targeted, personalized programs and campaigns that get better response rates.
Today’s increasingly robust, predictive account-based sales intelligence data requires marketing to think about longer-term consequences of activity and output.
SiriusDecisions’ brief, Value Proposition for Data Quality, helps marketers make a strong case for more sophisticated data offerings by communicating long-term ROI.
Deep account-based sales intelligence benefits an organization in the following ways.
Demand generation has always been a consideration, of course, and traditional metrics like open rates and deliverability won’t go away anytime soon. But better sales intelligence gives marketers fresh insight into sales-side metrics like stage-to-stage conversion, velocity, and cost per opportunity – areas where it’s easier to demonstrate ROI.
The better the quality of the intelligence, the easier it is to accelerate conversion and lower cost per opportunity.
2. Bigger impact on sales enablement
Historically, data issues – good or bad – have impacted top-of-funnel activities far more acutely (and visibly) than bottom-of-funnel sales activities. Business intelligence is often associated with awareness activities like email marketing; or on the sales side, with initial prospect targeting.
However, expanded data offerings are an opportunity for a direct impact on sales: Analysis of wins and losses can reveal buyer pain points, preferences, and assumptions that can be addressed by sales collateral such as battle cards and playbooks.
3. Simple, practical market analysis
Accurate data with expanded segmentation offers a more detailed picture of the market. This improves scoring, competitor insights … and can reveal new opportunities.
DiscoverOrg’s features let users define their ideal customer profile, find lookalike lists of prospects, and rank those prospects based on likelihood to buy today. It also allows you to size new market opportunities. For instance, if you’re looking to expand into the UK with a buyer profile similar to your North-American based prospects, you can leverage this intelligence to size and analyze your market opportunity.
4. Lower hard costs
Maintaining inaccurate and duplicate contact lists are expensive. In addition to lowering the cost of database maintenance by decreasing unnecessary bloat, marketing teams can consolidate vendors and negotiate lower pricing with fewer parties. These types of expenses are mitigated by deep, clean, robust data offerings.
5. Improve sales productivity
Sales teams must be able to trust the leads that come from marketing. When data is insufficient or inaccurate, sales spends critical time manually vetting contact data (consuming a third of their day, in many cases). This is particularly harmful to the bottom line when sales is responding to form-fill requests, where response time is critical.
6. Lower risks and cost associated with poor email deliverability
When email addresses are incorrect, domain authority takes a major hit due to the high number of email bounce-backs – which has tremendous downstream costs. Consumer trust and loyalty erode when segmentation is based on old data; for example, sending the wrong message to an existing customer.
You don’t know what you don’t know. But accurate, robust data limits unknowns, uncertainties, and assumptions.
7. Improved conversion and engagement
Sophisticated data offerings let marketing teams improve the customer experience with activities such as retargeting; personalized landing pages; and customized, dynamic web content – all shown to improve conversion to the next stage of the buying process. As customers engage and come to expect this kind of next-gen digital marketing, companies with outdated or skimpy data can’t possibly be competitive in the digital space.
8. Risk avoidance from better data
Reducing risk exposure is a case that’s rarely hard to make. SiriusDecisions shows that clean, accurate, robust data is exponentially easier to manage and mitigate risk. Data privacy regulations require secure acquisition, storage, use, and deletion of sensitive user information; it’s very difficult to maintain these standards with outdated data and tools.
Bad data exposes organizations to penalties, fines, degradation of brand reputation, customer attrition, weaker vendor negotiations, and much more.
A final marketing boon from the promise of better data: Leadership responds well to these kinds of downstream effects. Historically, long-term goals have sometimes been neglected in the snapshot provided traditional marketing metrics. These new benchmarks speak to forward-thinking goals leadership is more likely to support.
For high-growth companies in competitive markets, there’s a clear cost-benefit for investment in robust, accurate account-based sales intelligence. Enhanced data offerings and metrics that matter are a winning combination for B2B marketing departments and the sales teams they support.
The DiscoverOrg platform has already brought radical change to thousands of forward-thinking companies. Request a demo to see our sales intelligence in action.
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