Your Small Data Just Sucks

Written by Rand Schulman. Posted in Convergence Analytics

I was sitting in my office last week working on a targeted email when I realized something so fundamental – it’s a bit embarrassing to admit. As a data-driven marketing guy, you’d think I’d realize the most fundamental building block of any conversion starts with accurate “top of the funnel” CRM contact data. With garbage in you only get garbage out.

There’s a lot of talk about convergence of all things. There’s the convergence of all the systems we use, and the convergence of new roles – especially those of marketing and sales and building a culture of measurement.

As marketers struggle with all of the new tools, we need to review the most fundamental component of marketing, yet one of the most overlooked – quality information, our small data. Without good contact information these systems are just plain dumb, and they cost us more than they help. According to Gartner, contact information ages up to 50 percent in any year, becoming inaccurate and out of date, only serving to compound the issue. The top of the funnel data just has to be solid. And we have to be agile and act on it quickly.

A Typical Day
At our consulting company, Efectyv Digital, we use a number of tools to help us target and engage our current customers, and find new ones. We use a marketing automation system, in our case HubSpot, and a bunch of Google tools, SEO, pay-per-click (PPC), analytics, and Viralheat for social analytics. We also use various email products so we can test and optimize the send and open rates with tuned messages.

Like many of our clients, we are a B2B firm; we build marketing lists and segment and send targeted emails about our services to specific personas from those lists. The messages vary by role, industry, and need. They contain calls to action and other things you’d recognize as conversion events. We track our funnel and outbound conversions – and let me say we could do much better. Our list bounce rates are high and our open rates are low. We’ve hired an outbound lead generation person, and we’ve seen similar results.

We wondered if the issue was with our contact data or perhaps it was our offers and messages or timing (we just started using alerts)? To test, we decided to start one step at a time, and look specifically at the contact information contained within a few of the popular lead-generation tools to see why our conversion rates were so low.

It didn’t take us long to confirm, as we suspected, that our data just sucked and we needed to start making it better. Here’s our analysis. At least step one. We’ll always work on our messages.

The Simple Test
people-search-shutterstock-128521253While there are scores of products on the market, including LinkedIn, Zoom, and One Source, and some great new start-ups that have various degrees of content mash-ups like Tempo and Refresh, we chose to test three of the more popular systems that come integrated with CRM systems, including D&B 360, which has contact and company information – mostly generated manually; Data.com, the roots of which are crowdsourced with Jigsaw data acquired by Salesforce; and InsideView, which claims to rely on technology to deliver results. The levels of integration vary, depending on the CRM system, Dynamics, Oracle, Sugar, or Salesforce.

We used a real person and a real institution, in this case Krystin Mitchell, senior vice president of human resources at 7-Eleven Inc. Since 7-Eleven’s revenue is in excess of $80 billion and they’re public, we thought they might be a good test to see how we can find her in our test systems.

The results. So, where is Krystin? According to their current company Web page, she is indeed at 7-Eleven, but according to Data.com Krystin Mitchell is not included in a “Find Contacts” 7-Eleven search results. When we broadened it, we found there were 16 wrong results with her name, company, and email address. That’s crazy and not acceptable. I can see why our emails bounce.

We then tested the trusty old saw, D&B 360. Since much commerce is based on its data, it has to yield accurate results, right? D&B is the gold standard of contact data, the truth, built with human editorial control so we thought we’d get correct results. But, even with D&B, Krystin Mitchell is not included in “Build a List” of custom search results…although this time 65 wrong contacts came up instead.

To find her we needed to do a “general people in search,” but like in Data.com it yielded multiple/duplicate results, and different types of wrong contact info that tends to defeat the whole purpose of a contact tool. Interesting and again not acceptable. More bounces and wrong numbers.

We then moved to our free version of InsideView, which works with Salesforce.com. They are one of the companies that include data from multiple sources (thousands), and then validate it through a technology they call “entity triangulation.” Using analytics, this process is designed to determine the relative “truth” about people, content, and key event information. For our test about Krystin they got it right, listing her correct title and correct company and contact information, which match the company website and public disclosure. It was CRM Intelligence and we now use their Target product to build our lists and are getting much better results.

All in all we’ve analyzed vendor results many times, testing with different contacts, and companies and a great percent of the time fundamental results were different between vendors. I admit it’s hard to do, to really know where someone is, but that’s what we need and I am optimistic that there are new tools just coming to market, like marketing automation company Autopilot, releasing a new prospecting tool for sales and marketing that they claim is generating up to 42 percent reply rates on cold emails.

So, while this column is about conversion marketing and analytics, and I usually write about more meta subjects, I thought I’d share some personal real world issues that impact marketing, and ultimately sales. In this case our sales. We expect to at least double our conversation rate by spending more time creating quality data and lists.

money-falling-shutterstock-98093063We are drowning in data. It is no simple feat to filter this sea. But, it seems to me that we need to get the basics right about “small data” before we talk about optimizing big data, real-time data, and the impact of attribution models. B2B or B2C, quality contact information is fundamental. It’s best to walk before we run and finally sprint to the holy grail of real-time conversions, and revenue falling from the trees.

Images via Shutterstock.


The Stateless Internet Convergence of Things

Written by Rand Schulman. Posted in Convergence Analytics

As wearable technology goes mainstream, and as your car and home report on your behavior, the lines between analog and digital worlds blur, and we now have analytics for the real world, merging stateless Meta data and content marketing into the Internet Convergence of Things.

Chicago’s venerable Merchandise Mart, once the largest building in the world, is now at the leading edge of what I call the “Internet Convergence of Things;” it will serve as a good metaphor for this column where we see the joining of old and new.

Convergence is not located where you might imagine — in the tech hubs of Silicon Valley, Boston, or New York City — rather, in the big-shouldered magic kingdom where brands, advertising, and technology converge, and in the simplest form where content meets data.

At Efectyv Digital, we’ve done a fair amount of research about the convergence of new technologies in Convergence Analytics and I was asked to lead a discussion and present our findings to a combined group of agency executives and one of their big brand clients — whom they’ve represented since the earliest days of the Mart — to hear our vision for the future of the digital convergence, where a users’ “state” is meant to transcend and represent environments consisting of device, time, and place as the user moves about.

We can think of this state as context for our content marketing. This state may or may not be real-time, omni channel, mobile, and social or web, but rather is a convergence of all of these, and is organized around a clear objective or purpose. Of course it has to be measureable and thus optimizeable. I’ve written about this in “Marketing’s New Rules.”

I was taken to the corner conference room after a brief tour of the block-long agency designed by some famous Chicago architect, exposing color-coded tubes, blue-tinted glass, and steel beams dividing space with the view just outside the window of the iconoclastic gothic Tribune building, Chicago skyline, and lake. It was a physical convergence of old and new.

There were about 20 people gathered in the room, some from the consumer packaged goods [CPG] brand headquarters 100 miles away, and others from the agency. And like the building design, their roles converged — art and creative directors who measured and data base analysts who could write. Stan, one of the top creative directors, uses Omniture to test and optimize his team’s digital creative and share with the brand on a regular basis, while Karen, once a response marketer on the client side, now writes killer copy for the brand and still flies the BI application.

They gathered there to see my presentation and have a discussion about the utilization of transformative and converging technologies to help their CPG brands create more engagement, and how this engagement can help drive both in-store purchase and greater lifetime value [LTV], and which technologies and applications to use and to consider.

Why now? Over the last year, this brand had cracked the code on their customer loyalty base by matching opt-in customer ID, and profile information, with purchase data and was able to calculate the LTV of a cohort, (age, weight, gender) by segment.

They segmented their customer profile and digital behavior — mobile and web with social sharing, and their in-store behavior (duration, time, and location) with purchase history. Their goal was to both grow the customer base and purchase frequency, to understand the most valuable segments, and to understand online and offline behaviors measured by purchase history.

After this explanation, the conversation got interesting. They had known it was right time to optimize since a benchmark was established. To achieve that, the agency and brand wanted to create a way for the customer to engage more with the product during the in-store experience, and were experimenting with Augmented Reality [AR].


As marketers, they wanted to understand their most valuable customers and how they shopped. AR enables a kind of real-world tracking of humans, what they see and where they walk hyper-locally (within a foot). It can show us how they engage and help us to understand intent. While in its infancy, a good AR app can recognize objects, capture color, motion, angle, and sound and overlay or augment the reality of many things. The change in any of these dimensions can signal more or less engagement, or in other words, intent. I’ve written about this subject in “Augmented Reality Meets Artificial Intelligence.” The AR app functions like a page tag for the real world.

This is their convergence concept.

Remember, this is all opt-in, so we don’t have to deal with privacy issues and the mobile device (phone, Glass, or other wearable) is used for both GPS tracking and radio frequency [RF] in-store tracking, while the camera captures AR images. Why does the user opt in to something so personal? For this product, the brand promise is health and weight loss and the brand app allowed the user to track calories and activities (phone signals based on movement), log weight loss, and to share the success with their social network. In this case the phone acts like a Fitbit or other wearable device recording data.

The retailer’s application mashes up the user purchase history with other interesting bits of data, including real-world and in-store behavioral data, AR engagement data, and offers discounts and premiums for loyalty at checkout. The brand uses this information, with their opt-in profile data about the user, to trigger content marketing actions based on user preferences and attitudes to keep the user with the brand over time.

Additionally, they are exploring merging econometric data, like local weather conditions, mapped to user locations and actions, creating the fullest picture of the user for brand targeting, which can all be personalized in real-time campaigns for the stateless environment. As we collect more data in the future, we will be able to extrapolate large volumes of information from mobile and AR use and combine it with profile and purchase history. This is transformative.

The result: this brand is experiencing much longer app engagement with higher purchase conversions in the 40 test stores. It is being repeated all over the country, with equally stunning conversion results by other brands and agencies.

As wearable technology goes mainstream, and as your car and home report on your behavior, the lines between analog and digital worlds blur, and we now have analytics for the real world, merging stateless Meta data and content marketing into the Internet Convergence of Things. The only thing holding us back is the skill set of our converged workforce.

Seems like the old Merchandise Mart is still merchandising, but now its occupants are using a brawny form of 21st-century technology to get the heavy lifting done.


Building a Culture of Measurement

Written by Rand Schulman. Posted in Analytics, Convergence Analytics

convergenceI was sitting in my office the other morning, sipping a cup of coffee, when the phone rang. It was the chief executive (CEO) of a successful enterprise software company based in the Valley.

“Rand, we’re looking for a head of marketing to build a demand generation machine based on a scientific approach. Know anyone?” I thought, good question, but is he really looking for someone to head marketing, or is it some other role? Today, who is responsible for this activity across enterprise silos of data and new worlds of applied creativity to the various emerging channels, like mobile and social? Do I know anyone? Clearly, this CEO wants to build a company culture of measurement.

In our recent Convergence Analytics 2.0 report, we explore these evolving roles. In the past, this responsibility might have been owned by multiple people across the organization — the head of marketing, chief revenue officer, chief data officer (CDO), chief information offer, chief analytics officer, or other chief.

According to a recent Russell Reynolds article, there’s been a rise in the popularity of the chief digital officer role and last fall, Gartner predicted that 25 percent of organizations will have a CDO by 2015. That’s shaking up the corporate power structure in strange ways for many.

“The chief digital officer will prove to be the most exciting strategic role in the decade ahead,” says Gartner vice president, David Willis. “The chief digital officer plays in the place where the enterprise meets the customer, where the revenue is generated, and the mission accomplished. They’re in charge of digital business strategy.” Is that what we need now?

The role and reach of the CDO seems to be evolving as rapidly as everything else related to the digital, as it’s actually quite hard to find something that isn’t related to digital in some way these days. CDOs are appearing in companies, not as business unit owners, but as hybrid marketing-operating agents of change, seated next to the CEO at the corporate table.

Our CEO is looking to build a culture of measurement, which requires new thinking, as the tools didn’t even exist a few years ago. I told the CEO that it’s difficult to find the right marketing individual, as they need to have both analytic and creative skills to fill his demand. Yet today, those hybrid skill sets barely exist; they’re not being created in universities to address corporate demand for measureable results. Yet without those skills, it is impossible to fulfill the promise of the New Marketing Four Ps, the first “P” being people.

The new marketing leader will know when to hit the marketing gas pedal and how to analyze both program spend and macro shareholder value. They will be expert at driving company-wide KPI models that show when to invest in marketing — and when to pull back. When I was chief marketing officer (CMO) of WebSideStory, we used “magic SaaS” metrics that (then) Omniture CEO Josh James has written about and many follow today. We built a culture of measurement and after our IPO, were acquired by Omniture (now Adobe).

The new marketing leader will know how to create relevant content that converts. Like Innis and Ogilvy, they will be experts in communications and persuasion.

“Our colleagues want marketing professionals who can measure and optimize marketing effectiveness; the demand for those roles is essentially doubling annually,” says Alex Yoder, former CEO of Web Trends and director of The Oregon Association of Independent Colleges and Universities. “The amazing thing is this: despite a slow economy, the supply in these roles is just not there.”

US higher education, long a source of pride and differentiation across the globe, is undergoing a true crisis of value and identity. Pundits wonder whether universities are the next “bubble” of the US economy, while university students question whether their high-priced education and gargantuan debt loads — up 47 percent after inflation from 10 years ago — will position them for a college-worthy career.

Simply put, US universities are not adequately training students to meet the needs of the modern business. An imbalance exists between skills taught in classrooms and the skills sought in the marketplace. This imbalance is only accelerating with the rapid pace of change in technology and product innovation.

The silos at work in academia have also been a serious stumbling block for businesses, as our CEO is recognizing. In recent years, many organizations have revisited their organizational charts to fix the misalignment between marketing, engineering and operations silos.

Recently at SXSW in Austin, I sat on a panel with an ad agency CEO to debate the question, “Is too much math killing creativity?” The crowd leaned heavily toward creative, but when polled, attendees overwhelmingly said, “No.” They agreed that business value needs to be assigned to all creative and that conversions must be tracked through the sales funnel, from the very first level of engagement all the way through to revenue. The emerging paradigm in the news/media industry supports this; many are talking about a future that optimizes both ad spend and editorial content across acquisition channels, in “real-time,” based on economic demand functions.

To address the skills issue, I propose that we create a new major, as some institutions have, that spans existing schools and subjects, yet adds a modern shine to the old school plaque. I have proposed a content engineering degree, which leverages the existing curriculum and talent in business, liberal arts and engineering, yet also remains adaptable, to train students in new competencies as the market changes.

Clearly, we need to create a hybrid university graduate, perhaps a CMO, content engineer or CDO, who understands that the building of a business culture is based on both creativity and measurement, across business and demand channels, all driven by technology.

Our CEO is looking for an employee who has market-based skills. Anthony P. Carnevale, director of The Center on Education and the Workforce at Georgetown University, has called for a fundamental shift in thinking about the way students are educated. He writes, “The old model, where you go to college and then go out and find a job, is largely outmoded. It needs to be replaced with a new model, in which college years are spent explicitly preparing for an occupation.”

Innovation is part of the US DNA and has been for centuries. Today, our institutions of higher education are moving at a glacial pace, not keeping up with corporate demand for high-tech skills. Maybe the high-energy heat of market demand for digital sophisticates can “melt” the slow rate of change in higher education

I need to get back to that CEO with my recommendation. Not sure what I’ll say.

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