Elemetric: Valuable Lessons + What’s Next

A meditation on the past 10 months of building Elemetric — wins, losses, learnings, and an exciting path forward.

The Origin Story

I founded Elemetric in October 2016 during an EIR (Entrepreneur in Residence) stint at Datascope Analytics. Datascope is a company I’ve admired for a long time, and I was incredibly excited to work alongside the team as an EIR, with the explicit goal of harnessing the data science consulting expertise of Datascope into a scalable software product.

In the months leading up to Elemetric’s founding (August — October 2016), I worked alongside the Datascope team evaluating potential projects and eventually landing on the expansion of an interesting open source project called Catcorr.

The aim of Catcorr 2.0, rebranded as Elemetric, was to make the market research industry smarter, creating a software platform that would bring data science-like analytical capabilities to the market research industry — which remains reliant on antiquated techniques, processes, and toolkits.

You can read more about the original product in the release from Datascope’s blog (published way later) here.

The Opportunity and Challenges of Market Research

Market research is a weird industry, and one that manifests itself in different ways for different organizations.

The leaders of the market research space historically — large agencies like Ipsos, Kantar, IRI, and Nielsen — have managed this chaos by creating sprawling portfolios of “products”, as well as large professional services teams focused on bespoke client requests.

Our aim was to harness this chaos and “productize” the analytics component of these engagements— to begin, we talked to the users of research (brand managers and internal consumer insights teams), as well as the analytical engagement leads at the agencies.

In brand managers and analytics teams, we found an audience curious about technological innovation with a poignant self-awareness that the industry was falling behind — having not undergone the same radical changes as every other data-centric business in the past decade.

Along those lines, we conducted an early survey of 47 market research professionals and found that the average researcher used 2.4 tools to collect survey data and 2.6 tools to analyze data during a standard project. The redundancy and inefficiency is staggering, with 100% of respondents claiming that there was significant room for improvement in the current tools utilized.

We were excited — we’d found a fragmented space, with a huge amount of investment (industry-wide ~$42B a year) and an appetite for change.

So what’s the catch?

During this time, we also observed some worrisome things about the industry that we hadn’t expected up-front:

• From 2014–2017, 1.3B in venture capital was invested in market research startups; however, upon a closer look, significantly more than half of that amount went to established players founded prior to 2008. The two largest of these, Survey Monkey (founded 1999; raised $250M during the period) and Qualtrics (founded 2002; raised $330M during the period), have both become newly minted Unicorns, but only through a laborious 15+ year process for each. Very few deals have been done for companies founded since 2010, indicating an industry slow to adopt new technology.
• Data is becoming cheap and abundant; but not in market research. For those that have wrangled “big data”, or done extensive work in product, marketing, or advertising analytics, it’s clear that we’re living in a world of inexpensive and ubiquitous data. Data in market research, though, is time-consuming to gather and expensive to purchase. 3rd party survey responses typically range from $3–15 per complete, and subscriptions to platforms like Nielsen and IRI start at more than $50k for organizations. When data is expensive and scarce, it changes how its treated. Depth of analysis and narrative-driven storytelling become important; automation does not.
• Rapid prototyping and real-time feedback have made planning less important and “missing” with products or marketing strategies less painful. Small-to-midsize organizations, particularly, have mostly removed market research from their vernacular, opting for a landing page and a burst of targeted Facebook ads in lieu of a research-driven plan. Large organizations with complex supply chains still depend on market research for long-term planning, but increasingly these organizations are even struggling to foot the bill (see next bullet).
• Competition from direct-to-consumer rivals both large (Amazon, Jet.com) and small (Digital Native Brands like Blue Apron, Warby Parker, Dollar Shave Club, etc.) have traditional CPGs and market research agencies concerned. CRM and eCommerce data is cheap, robust, and abundant, allowing these organizations to make smarter product decisions in real-time, bypassing lengthy market research cycles. Additionally, the growth of Amazon’s marketplace, Shopify, and 3rd Party Logistics providers have greatly reduced the barrier to starting a brand — anyone with an idea can effectively play David to “Big CPG” Goliath.

So what does this mean for Elemetric?

In our first 6 months of working on Elemetric, we were able to build a compelling software platform and add value through hybrid consulting / software engagements with major companies; but myself and the team were becoming increasingly bearish on the market research industry, as a whole, and began looking for a new direction.

Since that time, Elemetric has gone through a series of minor pivots (pirouettes maybe?), exploring a solution broadly focused on segmentation analysis and automated insights in a post-research world.

The focus was on building a “next gen research platform” for the direct-to-consumer brands (particularly, DNVBs, which are a remarkably compelling subset of companies in the space).

The V2 of Elemetric worked like a B2C CRM focused on creating automated insight about a company’s user base from 1st party data that was already being gathered by existing systems, including:

• eCommerce data from Shopify, Stripe, or custom implementations
• User feedback data (NPS scores, order satisfaction, etc.)
• Social data mined from public data on Facebook, Twitter, etc.
• Product / SKU-level data being pulled from eCommerce system.
• Contact data pulled from support tickets, Intercom, Mailchimp, etc.

The value of this platform to companies was to create actionable, segmentation-based insights to impact customer acquisition (e.g. looking at CAC by segment) and long-term profitability (e.g LTV by segment). The plan was to build hooks into existing marketing automation and advertising platform to allow companies to take smarter, quicker actions based on real-time customer data.

After 50+ user interviews, leveraging the deep knowledge of IDEO, who became an investor in Elemetric through its SIR program, though, we were ultimately unable to find a marked customer need for this product.

In nearly every instance, the product felt like a “nice to have” rather than a “need to have” and increasingly seemed redundant with existing CRM, marketing automation, and advertising platforms — some of which already contain machine-learning-driven segmentation and insights platforms, mitigating the need for an additional tool like Elemetric.

In particular, we came across a few pseudo-competitive platforms that received rave reviews in the space, making themselves sticky by providing a lot of value to customers:

• Klaviyo — marketing automation + segmentation analysis for eCommerce
• Retention Science — AI-driven customer experience and automation platform
• Zaius — automation, attribution, and CRM platform for eCommerce

Ultimately, with V2 of Elemetric, we found that a “post-research” world is truly that — post-research.

The role of customer insights is being handled by a operational tools that are smartly integrating advanced data into their platforms, allowing insights to live close-by to the levers that can be pulled to make timely and actionable decisions.

These tools include marketing automation systems, eCommerce platforms, integrated support systems, and new breed agencies, which operate very differently than the stalwarts of the traditional research space.

I’m more than happy to meet and talk through these learnings in more depth with anyone that’s interested, but you’ll have to buy me a beer 🍺 (or at least a coffee).

The Silver Lining

The past few months have been a trying time for Elemetric; however, through the tumult, we’ve had some immense successes that have been critical in our realignment and that will continue to pay dividends with the company’s direction moving forward.

Specifically, I’d like to thank:

• Datascope Analytics and Dean Malmgren — from the beginning, Dean and Datascope have provided Elemetric with partnership, ideation, office space, unconditional support, development resources, and countless hours of brainstorming have been foundational to our successes and perseverance through trying times.
• IDEO and Justin Massa — The IDEO startup-in-residence program made me a better entrepreneur, and helped Elemetric navigate a major change in direction. Coming out of this program, I better understand how to talk to customers, think creatively, and focus on the things that matter in building great products. Similarly, Justin is someone every entrepreneur in Chicago should know and look to for guidance.
• Techstars and Logan Lahive — Techstars, though only halfway complete, has completely changed the way I approach entrepreneurship. In 7 short weeks, I’ve greatly expanded my rolodex, become impossibly energized about building a great company, and gained the confidence to write this post and completely shift my focus to the future of the company. I’d like to especially thank Logan, the MD of Techstars Chicago for being a champion for the new version of Elemetric.

Now What?

I wrote a companion post about our new direction — check it out here:

A New Direction for Elemetric — Data on the Blockchain

Thanks to everyone not mentioned here for the support, connections, wisdom, and time. I’d especially like to thank everyone involved in Techstars, including the associates, leadership, and mentors, who have been instrumental in helping the company through the hard times, and helping us plan for future success!