When it comes to CRM and MAS database accuracy, traditional thinking places the optimal range between something more than 10% but not much above 20%. If accuracy falls below 10%, the results of marketing programs are so disastrous you don’t need state-of-the-art analytics to see it.
At the same time, it has been prohibitively expensive to raise B2B database accuracy above 20%. The rule of thumb is that for every percentage increase in accuracy above the magical 20%, a company can expect to increase overhead by approximately 1%.
So, when it comes to B2B data, inaccuracy, and lack of precision, is an accepted affliction. B2B data is terrible. And it’s been terrible for since the beginning of marketing and sales software.
John Wanamaker first said it a century ago, but marketing and sales leaders are thinking the same thing today: “I know half the money I spend on advertising is wasted, but I can never find out which half.”
Good data, clean data, and accurate data make a critical difference to how CMOs and marketing VPs are evaluated (and compensated). The reputation of a company, it’s brand, and, ultimately, its bottom line depend on data-quality. Attribution tools and analytics reveal just how much of marketing budget and potential ROI goes up in smoke every quarter.
The good news is that the industry is changing, and I see LeadGenius at the apex of much of that change. Sales and marketing need next generation data, and I’m delighted to join as VP of Product what I consider to be the premiere next generation data company.
The Case for Volumetrics Weakens
Marketers haven’t always cared about data accuracy. For the longest time, companies were able to play the numbers game and seemingly come out ahead.
“I don’t care about accuracy,” was marketing’s clarion cry. “I don’t care about delivery rates. All I need is data…lots and lots of data.” After all, when you can’t measure the results, precision isn’t such a problem.
As long as direct mail costs were low enough, an average response rate of 1% to 3% was fine. And with the advent of email marketing tools ranging from autoresponders to marketing automation, marketers could continue to rely on volume—with “Big Data” vendors filling up the hoppers of marketing automation systems with any and every email addresses they could find.
It wasn’t really working, but nobody really cared. No one knew any better.
This was the marketing space I entered about 10 years ago. My career has followed a trajectory that closely parallels the advances in tools, the rise of cloud services, the explosion of Big Data and the ability to measure marketing efforts. Each advance has contributed to growing sophistication in the sales and marketing space.
I started in marketing as an online marketing web specialist at Genius.com then a web designer/developer at Marketo. Upon returning to Genius.com as Creative Director, I became increasingly focused on marketing execution with a focus on user interfaces and user experience.
At LeadRocket, an evolution of the Genius Tracker (a first-of-its-kind sales outbound engagement tool ultimately acquired by CallidusCloud) I drove product vision and strategy on marketing automation and helped bring the product functionality into Gmail via a Chrome extension.
I dealt with the industry-pervading issues with data quality in previous roles, but it was my time as Head of Product and UX for BrightFunnel that effectively put a giant magnifying glass on the problem of bad data. At Brightfunnel, we had to deal with the problem head on and I discovered just how large a challenge it really is.
It’s a bit ironic because marketing executives, and particularly CMOs, thought that marketing attribution would help showcase their efforts. Instead, it has clearly demonstrated just how poorly their marketing execution and results have been, thanks in large part to the mess that has been in both actionable and operational data.
All this has come to light in the last couple of years. As recently as 2014, a Forrester survey found that half of marketing executives thought it was “difficult” to establish attribution between marketing activity and revenue.
Attribution software has left CMOs and VPs vulnerable. More powerful and accessible marketing attribution software has correlated to decline in marketing executive job tenure. Bad data and resulting poor campaign performance shows up like crime scene evidence under a blacklight. In the UK, average tenure is only 18 months. In the United States, it’s longer but dropping: Having gone from a high of 48 months in 2014 to 42 months in 2016.
Although we’ve shown light on the problem, there’s a long way to go. Year after year, survey after survey, concerns regarding data accuracy continue to head the lists:
- In 2015, BrightTALK reported 24% of marketers couldn’t even determine if their marketing efforts contributed to closed-won business.
- In the 2016 State of Lead Generation survey, “improving the quality of leads” was both the most important objective (77%) and the greatest barrier (53%) to generating better results.
- And according to the State of Pipeline Marketing 2016, referrals and word of mouth (WOM) marketing was the single greatest revenue channel (22.3%). Revenue from WOM beat email marketing (8.8%) and SEO and content marketing (tied at 9.1%).
And there’s more at stake than revenue and ROI.
When your customers and prospects are receiving four…five…10…or more irrelevant (untargeted) and mistargeted messages because your contact data and leads aren’t accurate, then your brand, your reputation are at risk. This translates to poor marks for customer service, being ignored by the people you want to reach with marketing programs going forward and having to spend additional money cleaning up the data both manually and with software.
During the last 10 years, first-wave data companies delivered the volume marketers needed to power their early executional and automation tools. Those vendors are being consolidated into larger platforms. And during the next 10 years we’ll see a lot of this get sorted out.
Why LeadGenius Is The Next Generation Data Company
As someone who has grown along with this sales-marketing-data space, I can see through the prism of my own experiences the capacity and capabilities LeadGenius brings to the challenge of delivering quality (accurate) data in large volumes (at scale). This is what makes LeadGenius a next generation data company.
The fact that LeadGenius is solving and industry-wide challenge through a combination of human intuition and machine language…well that’s exciting.
Before getting into the power of human intuition, there’s the social mission at LeadGenius. It’s the perfect marriage of strong social mission and doing something soul freeing. CEO and Co-Founder, Prayag Narula, says providing good jobs around the country and world to areas that haven’t traditionally had easy access to opportunities, it’s the right thing to do.
It also makes good business sense. It’s LeadGenius’s researcher community— the engine that provides human intuition at scale—that delivers:
- The consultative “first mile” that applies intelligence about the marketplace to help educate clients and deliver a more sophisticated ICP (ideal customer profile).
- The accuracy that makes all the difference in terms of deliverability and a format that is easily utilized. To borrow from field of artificial intelligence, that’s the “last mile,” and it’s usually the toughest.
With 500-plus researchers in the LeadGenius crowd making real-world decisions and creating applicable workflows, raw data is transformed into actionable information. Volume becomes meaningful again when quality-assurance is scalable and cost effective.
Human intuition further has the capability to support multiple custom data points and custom data sets analysis—something even the best AI cannot deliver on its own. Combine this with business graphs—networks of the connected universe (e.g., a company’s extended network of vendors, partners, competition, customers and more) and the different ways you can connect data points—and ICPs provide sophisticated insights into the messaging, personalization and content that closes business and delivers ROI.
I see the opportunity and the reality of LeadGenius providing marketing and sales with the solution set they need to get to the next level. Succeeding in this space means that in an ideal universe people are touched less frequently regarding things they’re not interested in. Less friction is better. When marketing automation uses accurate data that is the result of human interaction and intuition, your brand and your credibility go up.
What You Can Do Today
Collectively we’re still in the awkward “tweenager” stage.
We have most the tools we need to execute but the data is, for the most part, still terrible. It’s going to fall to the next generation data companies to not only supply the market with high-quality data, but also educate and facilitate, better use of that data to help boost business’s bottom line.
In the meantime, here are some steps that will help make the difference:
- Quit Spray and Pray: Traditional demand generation (spray and pray) must go away. Dialing for dollars and email blasts and betting on volume to make up for it is not only going to NOT deliver results, companies risk hurting their brand as well.
- Define Your Ideal Customer Profile: Companies need to put greater emphasis on creating a sophisticated ICP. As we move away from spray and pray, we can still cast a wide net. Start by identifying your broad Total Addressable Market (TAM). Then, within that arena, filter and segment deeper, more sophisticated, Ideal Customer Profiles (ICPs). These are the target verticals and personas within your TAM. Once you can identify them, you can personalize your messaging and content to specific needs.
- Define Your Pipeline Strategy (The First Mile): Look for a data vendor that takes an advisory or consultative approach to help you define your data (or more accurately your pipeline) strategy. This is the first mile in your data strategy, and you want to work with a company that can help you validate your ICP and refine your go-to-market strategy.
- Think About Your Data Stack (The Last Mile): The most sophisticated marketing and sales programs know that they are not going to find all their contact data from one source. They need three, four, maybe more resources. Just as they need a marketing stack and a sales stack, they need a data stack of tools and services. And that data stack is not one size fits all. Each sales and marketing operation needs to layer companies and information to create its own best-of-breed data stack. Managing all those vendors is a job—verifying, identifying overlaps and figuring out how to operationalize it. Many companies already are using some combination of software and manual checks to clean their data. Precision requires that human touch.
- Align Sales and Marketing: As long as sales and marketing are compensated differently—with sales comped on revenue and marketing most often comped on pipeline—it will be difficult to totally align the two. But it will happen, and we’re starting to see more similar accountability. Revenue is the ultimate alignment that makes a lot of the confusion with objectives and terminology and tasks disappear. Within 10 years, marketing and sales will operate in a similar capacity. Don’t think it will take that long? Consider that only a year ago an Ebiquity/CMO Council study found that just 3% of marketers reported that their data is “completely integrated and aligned.”
- Think Account-Based Everything: It’s not a new concept, but the account-based approach is gaining traction. It’s a common-sense approach that requires really good data. If you’re thinking account-based marketing and sales then you’re automatically going to focus on doing what you can to improve the quality and accuracy of your data. ABM requires going deep, really deep, into the signals and triggers behind sales as well as demographics and firmographics to create a rich ICP.
People are clearly willing to buy data. All sorts of companies — from small-time list brokers and big data vendors, to outsourced lead gen teams and purportedly AI-powered SaaS platforms — are rushing to fill MarTech’s need for better data.
As more sophisticated customers enter the market, the entire industry will be elevated. In the end, we will level-up the entire market space.