3 Everlasting Differentiators in a World of Commoditization

Now that you’re through the first quarter of 2016, it’s time for this year’s rendition of trends in marketing technology. One ongoing development that spans all industries is the commoditization of key elements used to define modern software: data, visualizations, and algorithms. Each of these components began as a highly touted differentiator, but today’s rapidly evolving ecosystem has quickly turned them into a table stake feature. So, what’s left to differentiate?

Data, Visualizations, and Algorithms

• Data. With the continued reduction in data storage and computing costs, coupled with data vendors fire-selling their proprietary databases to any software company, having common data has become a commodity. A multitude of data vendors sell similar datasets, and you can teach an intern to scrape publicly accessible web data. The effect is that many software companies now leverage very similar data sets. Tech investor Boris Wertz, from Version One Ventures, recently said that having unique solutions with defined data sets is the key, and even trying to build a machine-learning operation on top of common public data is not a defensible market position.
• Visualizations. Visualizations first emerged as vital eye candy that could encourage the adoption of business intelligence in enterprise companies. While some execute better than others, donut charts, bar charts and exploded pie charts are nothing new, making there way into even the most basic business intelligence applications. “Analytics is old news” rang true in nearly every session among panelists and analysts at the 2016 Gartner Business Intelligence and Analytics Summit.
• Algorithms! Algorithms, machine learning, data science–the newest of the commoditized differentiators that seemingly every software startup is boasting. Algorithms were developed more than 30 years ago to help computer programmers build statistical routines that provided consistency in a variety of hardware. In today’s cloud-based world of open source code bases, algorithms too are a commodity. Most platforms built to ‘predict’ use the exact same set of algorithms including logistic regressions, Naive Bayes classifiers, Random Forests, and more.

Amongst the 3800+ technology vendors, I’d estimate 80% offer 1 out of 3 of these core capabilities, 30% 2 out of 3, and less than 5% 3 out of 3 — which is still almost 200 companies. This article is not to help buyers assess vendors, so it’s important to note that not all solutions are created equal — execution is everything and many solve niche business objectives.

Data Network Effects, Integrations, and Ecosystems

So, how do you create long-term differentiation in the face of constant commoditization?

• Data Network Effects. You may be familiar with network effects — a product or service increases in value as more people begin using it. Facebook is a good example. It gained huge value when it went from being a site for college students to achieving worldwide popularity in every age group. Data network effects are similar — as users enter more network data, the applications become smarter. This results in more value for the user and allows for vendors to create new capabilities, which makes it increasingly difficult for competitors to gain market share. It is not just about having more data — value comes when it is combined with machine learning and interfaces that can deliver actionable insights. But as we discussed, those are easy to build ;). Data network effects are similar to a snowball effect — described as a “winner takes all” strategy. Peter Thiel lists data network effects as one of the defining factors in becoming a monopoly.
• Integrations. There is no such thing as an end-to-end solution. Scott Brinker’s recently released 2016 Marketing Technology Landscape Supergraphic is an indication that no companies solves everything. With such an overwhelming number of providers, companies must focus on specific use cases in order to resonate with overwhelmed users. By seamlessly connecting the various technologies required to execute a use case, companies can gain traction by actually delivering on “actionability” rather than complicating users’ workflows. Actions lead to results, which leads to advocacy, which makes it difficult for competitors to enter the market. You can do this by marrying the best applications and open platforms, not building “closed garden” systems.
• Ecosystems. “Software is eating the world.” But with so much software, users are suffering from obesity and decision paralysis. Thousands of options are eating away at our ability to choose. Am I buying the right stuff, effectively implementing it, maximizing its value, and still able to do the few things left up to humans? I see many companies throw multiple nearly identical technologies at one problem without arriving at a solution. It’s like shopping at the supermarket when you’re hungry — you buy a bunch of stuff you don’t really need and it ends going to waste. Companies can differentiate by rescuing their buyers from being eaten alive by the software landscape. Offer robust customer success and support programs, partner with agencies & consultants, build consortiums of complementary solutions, host user events, create content that actually helps people do their job. Salesforce has mastered building an ecosystem. Users are craving guidance and are willing to pay for it.

Here’s the kicker: commoditization will never stop. There will always be a buzz, followed soon after by a “so what”. Network effects, integrations, and ecosystems are not easy to create. In fact, they are probably the hardest things to create beyond a product that has true market-fit. But creating a defensible, long-lasting business in an ultra-competitive landscape isn’t going to be easy. Who knows what shiny new ‘differentiators’ 2016 will bring!