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There’s a timeworn argument between the marketing department and the sales department. Marketing complains that the sales team isn’t following up the bushels of leads it gathers. Sales complains that most of marketing’s leads are of such poor quality they aren’t worth the effort of pursuit. It’s like an endless tennis match where blame is the ball. Meanwhile, opportunities are being lost and revenue is stagnant—at best. It’s the fundamental reason for lead scoring: arriving at a set of qualifications that measure the strength and value of a lead.
Directing business from the wide end of the sales funnel to the narrow end is all about having one’s corporate priorities straight, but those priorities change from industry to industry, and from company to company. This is a story about what goes into getting leads qualified, codified, and ranked so that the juiciest opportunities are always the first to get pounced upon, as seen by four industry experts.
IT'S A MATTER OF (BUSINESS) INTELLIGENCE
“There’s huge focus on analyzing the customer base in a real-time manner,” says Kevin Bandy, partner at global consultancy Accenture. “Many companies have invested in Web analytics and business intelligence, but they must use it to identify new routes to market. If you’re not linking BI to [specific] customer data, you don’t know which customers fit into which analytical cohort.”
Not only is marketing responsible to the company as a whole, its first “customer” is the sales department, and its value to sales is measured in actionable leads. “There’s an enormous amount of expenditure on MROI—marketing return on investment—and it’s growing every year because the customer base is growing,” Bandy says. “If analytics aren’t tied to customer data, there’s no means of proving MROI.” While this may sound like a marketing or broad strategic play, it has equal value in the sales trenches. Sales must understand what’s coming in from marketing, and have the ability to continue the analysis so that leads aren’t static and dead.
So what makes a lead good? This is the central question that lead-scoring applications try to help businesses answer. Unfortunately, the answer is usually, “It depends.” That’s not a matter of snark—a lead that’s good in one industry segment, or for one company, or at one time of year, may be rubbish elsewhere.
“There is no single definition of a ‘good lead,' " says Mike Vannoy, a partner with SalesEngine International, a maker of B2B lead-scoring applications. “We make fun of that idea around the office.” Jokes aside, Vannoy says there are two serious considerations in lead scoring:
- First is consensus on business needs. “It’s whatever sales and marketing agree on it to be; a midsize tech company might have a different definition than a $10 million startup where every lead has to be solid,” Vannoy says. “But there must be agreement.” Without it, the two sides get stuck in the tennis match as each tries to pursue different goals.
- The second is the idea of explicit-versus-implicit lead qualification. It’s not always easy to grasp. “People get this conceptually, but don’t practice it,” Vannoy says. “Explicit lead scoring has been around for a long time—it should be a no-brainer. It’s all the things you can just query on ZoomInfo,” such as company, sector, job title, and perhaps stated need for a product or service. “Implicit lead scoring is the client activity that shows interest in your product or service, like downloads or Web-site activity.”
Of the two flavors of lead qualification, Vannoy strongly favors one side. “If you don’t include implicit scoring as a real-time, fluid thing,” he says, “you’re missing a lot of the point of scoring.” As an example, he describes two prospects, each of whom downloads a vendor’s white paper. In explicit terms, those are two equally valuable leads. Then imagine two other prospects downloading the white paper: One doesn’t open it, while the other opens it, confirms her email address, and forwards the document to others. Which one are you going to concentrate on more? Which one is more valuable?
WHAT DO WE REALLY KNOW ABOUT THE LEADS?
As technology advances and becomes more affordable, there has been a move away from sole reliance on explicit qualification and static scoring. “If your score is just a single number, and that’s what the salespeople see, they just don’t know what went into it,” says Jim Meyer, vice president and general manager of eTrigue, a provider of on-demand lead-analysis tools. “That’s a problem with single-score solutions. An intern might have a low demographic score, but a high activity score—adding up to 100. A CEO, on the other hand, would likely have a high demographic score and a low activity score—also adding to 100. How can you tell the difference?”
Like almost anybody you might ask, Meyer is of the “it depends” school when it comes to judging a lead. “I see many ways people choose to score—it’s all over the map,” he says. “Plus, any model you make to score leads is going to change over time.” He notes that larger companies “tend to be more formal about lead scoring, so they score more often,” but the criteria are not set in stone for any industry.
Change over time is an important concept in lead scoring, and it’s also one on which eTrigue focuses. Not only do a company’s needs (and thus its scoring criteria) change over its lifetime, but the scores themselves need to reflect those changes for an accurate picture of a lead’s value. “Score as you go along, and adjust the scoring—but do it retroactively,” Meyer says. Doing so shows the present value of old business, making it easier to understand the nature of change. If webinars are performing badly, for instance, lower their value in the scoring system, but change the older scores as well so you don’t make decisions comparing against old data.
Most readers are familiar with the mantra “Know Thy Customer,” and it’s a good one. But perhaps it should be expanded, to “Know Thy Customer As Thyself.” A clear understanding of your own value can only help you know which prospects are the best fit and most likely win. “Imagine an emerging business, coming to market with a product, as a Venn diagram of the market’s needs, your capabilities, and your competition,” SalesEngine’s Vannoy suggests. “You must consider your competition—if you go after business where you don’t have a compelling advantage, you can tee up a lot of opportunities for your competitors to win. That’s great if you get paid on the number of leads generated, but it’s a bad business plan.”
Rather than give customers away, Vannoy says enlightened lead scoring—where you consider all the cards on the table, including the competition’s—is much more likely to lead to success. “Focus on what your competitors can’t do. Blow that out, make it big for you, and pursue the prospects that need it.”
Meyer insists that custom scoring for particular markets is necessary, and there can be no one-size-fits-all solution to lead scoring. He also knows that, contrary to popular sentiment, it’s not always best to jump on the freshest leads immediately; wine that’s poured too soon is just grape juice. “Marketing tends to overvalue individual events, skew the weighting because of one thing, and hit the prospect too early,” he says. “Giving the salesperson a detailed view of what makes up a score is an important trend. Complete detail on a prospect is very useful when you make the call.”
TIMING IS EVERYTHING
Since the discussion of lead scoring includes the age of the lead and how active it’s been, it’s no surprise that when can be just as important as what or how.
“Many companies routinely give all the contacts from a trade show, webinar, or other demand-generation campaign to sales or telemarketing to call,” says Jon Miller, vice president of marketing for Marketo, a vendor of marketing automation software. “But just getting their badge scanned or downloading a white paper does not mean that person wants or is ready for a sales call. They may be qualified to be a potential customer one day for your product or service, but right now most of them are not yet ‘sales-ready.' " Marketo’s research indicates that typically fewer than 25 percent of new prospects meet the criteria for “sales ready” and fewer than 5 percent are active opportunities. “So,” Miller asks, “is it really a good idea to spend 75 percent of your time calling—and annoying—the wrong people?”
The answer, of course, is “No.”
“I believe companies should wait until the prospect also shows the engagement and behaviors that indicate they are sales-ready,” Miller continues. In other words, cultivate leads over time and pass them to sales when they’re ripe. “This not only prevents the prospect from having a bad reaction to an unwanted interruption, it also improves sales productivity—which can lead to 40 percent or more revenue growth.”
(Even if Miller’s right about the 40 percent bump provided by sales productivity, that still may not be the single-most influential move you could make with regard to revenue. Once your shock wears off, see “The Untold Secret to Lead Scoring,” at the end of this article, for the key to a potential 66 percent increase.)
Miller knows there are reasons why sales reps can’t—shouldn’t—call everyone. The easiest way to annoy potential customers and your sales team at the same time is to prematurely label new contacts “leads” and have sales call them too early. When the sales team calls everyone—including the unlikely prospects—it (a) perpetuates the impression that all marketing leads are “no good” and (b) makes them more likely to ignore the ones that are good.
And Miller suggests a major flaw inherent in the most-common demand-generation programs, such as trade shows and webinars: These efforts create leads in large batches. Given all at once to sales, the resulting flood of leads means a lot of good leads don’t get contacted in a timely fashion as sales works through the list. Then, once the list has been touched, sales looks for their next “list” to call and often ends up cold-calling completely unengaged prospects in the hope of creating opportunity. This is a much less efficient use of time compared to following up with warm, engaged, and qualified leads.
As a marketer himself, Miller laments the fact that many companies stop marketing to leads once they’re passed off to sales—a terrible notion, he says. Contacts that could develop over time into real leads end up sitting idle in a sales rep’s contact list without any active effort to stay in touch or accelerate the buying process. Instead, leads that are deemed “not sales ready” should be recycled back to marketing for further nurturing.
Vannoy provides another angle on timing. “Most organizations are focused on what’s hot now. Only a certain percentage of companies in your market are looking for product at any given time,” he says. This is why it’s important that leads be dynamic, the scores changing with age and new data. “If scoring is implemented properly over time, you can show who’s worth nurturing.”
Lead scoring, when done right and done consistently, can bring new power to a sales organization and make its bond with marketing much tighter. Using the intelligence gleaned from lead scoring, you might even gain new insights about your company. “Do you know where you lose prospects?” Vannoy asks. “Most sales professionals can tell you ‘X percent leave at Stage 9 of the process,’ but what percent leave before Stage 1?” He says modern lead scoring can help answer that, if you’re ready for it: “It takes a fundamental change in how you run your business—how you train and deploy salespeople.”
SIDEBAR: The Untold Secret to Lead Scoring
The two magic words? “Data” and “quality.”
What’s lead scoring got to do with data quality? Way more than you think, according to a recent report.
In fact, the SiriusDecisions study, “The Impact of Bad Data on Demand Creation,” shows that following best practices in data quality generates a 66 percent increase in revenue, thanks to improvements in lead scoring. In today’s economic climate, that’s nothing to sneeze at.
The level of dirty data is what separates typical B2B organizations from those that follow best practices. Even at process-optimized companies, 10 percent of customer and prospect records contain critical data errors, according to Sirius. These errors can include incorrect demographic data, out-of-date disposition, and other basic flaws. At the average company, however—one that fails to follow best practices for data management—the data-error rate can balloon to as high as 25 percent. In either case, the amount of data doubles every 12 months to 18 months, resulting in a comparable rise in overall data-cleansing costs—while potential revenue from those flawed records is never realized. This is summarized by what the Sirius report calls the “1-10-100” rule: “It takes $1 to verify a record as it is entered, $10 to cleanse and de-dupe it, and $100 if nothing is done, as the ramifications of the mistakes are felt over and over again.”
“Despite its criticality to the business, the databases of B2B organizations are akin to an attic, filled with contents that have not been properly labeled, managed, and maintained,” writes Jonathan Block, author of the report and senior director of research at SiriusDecisions. “Most B2B marketing executives lament the status of their databases, but have had a difficult time convincing senior management of the need not just to temporarily clean things up but to permanently change the manner in which data is treated.”
There are several key areas where superior data management can have discrete benefits, according to the report. These follow the SiriusDecisions Demand Creation Waterfall methodology:
- From inquiry to marketing-qualified lead: It’s most cost-effective to manage data at this early stage, rather than let flawed information seep through the organization. A data strategy that solves conflicts at the source can lead to a 25 percent increase in converting inquiries to marketing-qualified leads.
- From marketing-qualified lead to sales-accepted lead: Bad source data is compounded by the use of multiple databases and formats, leading to distrust of marketing’s work by sales. Unifying the data, whether into one database or by using technology for virtual integration, can lead to a 12.5 percent uplift in conversion rates to the next stage.
- From sales-accepted lead to sales-qualified lead: Scoring becomes important at this stage, as the sales team goes to work on the leads it can use—and returns others to the marketing team for further nurturing. Clean data can reduce by 5 percent the time spent conducting the kind of additional research that precedes initial contact with a prospect.
- From sales-qualified lead to close: Benefits seen between sales qualification and close magnify those accumulated during the previous stages, as salespeople continually update the status and disposition of the potential customers. “Given that the average field-marketing function spends no more than 10 percent of its budget in support of this final conversion, accurate data is a must for applying the right tools and resources to the right audience at the right stage of the buying cycle,” Block writes. A single system of record to keep marketing and sales on the same page—cultivated by timely updates by all involved parties—is critical.
The impact of these abstract concepts—the true value of data management—becomes quite clear as soon as real numbers are applied: From a prospect database of 100,000 names, an organization utilizing best practices will have 90,000 usable records versus a typical company’s 75,000; at every stage thereafter, the strong company has a larger pool of prospects with a higher probability of closing. In the end, SiriusDecisions can show 66 percent more revenue for the company with high-quality data management.
“For those marketing executives having problems convincing senior management that a permanent process upgrade—rather than ‘quick fix’—will pay big dividends in the long run, this is the kind of eye-opening statistic that should prove invaluable,” Block writes.
So forget the old argument of whether it’s the sales department or the marketing department that’s responsible for lead quality. “A best-in-class data strategy is shared by marketing and sales, and is focused on quality from [inquiry] to close,” Block writes. “Although it is a job that consumes both money and time, paying more attention to data quality is not only worth it, it is something that your organization simply can’t afford not to do.”
Contact Senior Editor Marshall Lager at mlager@destinationCRM.com.
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