Growthverse Spotlight: RichRelevance
I’m thrilled to introduce today’s featured company on the Growthverse Spotlight: RichRelevance. I go way back with the founder of RichRelevance, David “Selly” Selinger, so naturally I was excited to see RichRelevance was part of the Growthverse. We had the chance to catch up with Chief Product Officer Mahesh Tyagarajan to hear some of his insights on marketing automation and the customer experience.
Where do you see the marketing automation industry in 5 years?
Marketing automation will favor platforms that are predictive-first, open and agile:
Predictive models will employ advanced machine learning in order to test and learn which actions are most effective, and predict which one will perform best for each customer interaction. They will account for the subtlest changes in behavior, inventory, pricing and more, in order to capture and react to micro-trends as they occur.
Emerging machine learning technologies, like Deep Nets, will be key in both “out-of-the-box” capabilities, but will also need to integrate into the rapidly changing and heterogeneous machine learning ecosystem.
The ecosystem will be open and offer services that can be orchestrated freely, with well-documented, clean APIs that allow third parties to build customized, best-in-class experiences. An SOA-based architecture will be the core of this platform, providing agility and speed to market.
A new market dynamic will be driven by privacy legislation (e.g., the core reason DMPs exist), speed to market/competition and cost, in that order.
Privacy legislation is forcing certain functions/capabilities to be centralized for focused accountability and integration. We will likely see a wave of encryption and security enter the market, dominating the data management space and driving integration into the adjacencies.
Speed to market will be key. Unified platforms with lightweight, well-documented integrations into both cloud and on-premise systems will be at the center of driving decision-making for marketers—these will be the new dashboards providing the equivalent of “trading desks” for paid media but overseeing all customer-facing digital marketing.
Finally, the low cost of cloud-based systems will continue to drive innovation and convergence of capabilities. The lines of what you buy from whom will grow blurrier—emerging niche players will continue to grow and larger players will continue to struggle to compete organically so we will see continued acquisitions in the space.
What distinguishes RichRelevance from other products in that space?
Research has shown that omnichannel shoppers have 30% higher lifetime value than single-channel shoppers—and our customers dominate the field when it comes to omnichannel success.
We’re uniquely positioned to help retailers expand and strengthen their personalization through our ability to unify customer and product data stored in disparate systems. For example, online systems often can't access store systems. RichRelevance can unify multiple customer IDs from different channels, sessions and devices to create a single user profile through probabilistic matching. We are also able to aggregate product catalogs to become the central data repository, accessible from any channel at any given time.
How is the customer experience changing, particularly with the development of data aggregation?
The age of Big Data has ushered in a tremendous increase in the transactional and shopper data available to businesses. The surge of data has created immense choice insofar as transactional channels for consumers (e.g., a la Google Adwords and PLAs, mobile apps), but has also diluted the marketer’s definition of loyalty and brand.
Today’s super consumer is hyper-connected and in control of the use of her data in the world around her. As a result, the definition of customer loyalty has dramatically changed, and businesses still need to change with the customer’s changing habits. This constantly evolving customer ecosystem means that businesses must solve a very hard problem: How to use all these data to generate more revenue—achieving perfect efficiency—while simultaneously tackling the problem of cultivating loyalty with these same customers.
A lot of businesses have confused short-term sales and data optimization for profitability. We saw this in the huge spike in SEM businesses with retailers believing they were buying loyal customer traffic; this was however, quickly followed by a huge selling-off and marginalization of these technologies. While an important tactic, these channels deliver sales, not strategic loyalty or long-term profit.
What challenges are you facing in the marketing automation industry?
The true Alpha-winners in the next generation of marketers will focus on learning how to unlock the power of these data to create differentiation and personalization. They will need to master tactics like SEM to be in the top quartile of performance, but will design their organizations, their infrastructure and their metrics to ensure that the lion’s share of their effort goes into winning the long-term customer loyalty game. Where the rubber hits the road: The great marketers will trade 1% of tactical revenue lift for 0.5% increase in loyalty.
The data dilemma remains a significant challenge for many organizations. The amount of data being tracked (clicks, time spent on site, store purchases etc.) and the amount of data being generated is anticipated to increase 20x in the next 5 years. On average, today’s enterprise runs 30 marketing systems, double the number from 10 years ago. Siloed in disparate systems, this customer data not only requires multiple points of integration, but also perpetuates disjointed conversations with the same customer. For example, a retailer may have one database feeding tailored email offers; another system managed by merchandising for upsell, recommendations and content; and another handling loyalty.
What are your favorite operations and marketing technology platforms and tools?
Ultimately, enterprises need unified data management and analytics platforms that serve as a distinct layer (essentially a data “traffic cop”) which can scale with marketing data sources and engagement applications. Simultaneously, marketers need tools that transcend online and offline boundaries, using data to apply personalization across the entire customer life cycle.
Google’s toolkit continues to be an inspiration to myself and all technologists. The Google Analytics toolkit has raised the bar for all analytics players and I hope they continue to do so.
Having said that, most enterprise software companies develop their own custom analytics tools built on Big Data platforms and using open source toolkits and the next generation of BI/analytics tools, such as the one we use – ThoughtSpot.
Do you have any thoughts about the future of the martech landscape, or why it is growing at such an incredible pace?
The landscape is growing with consumer confidence. That is both a positive and a negative thing—even as consumer confidence has been riding an incredible bull market, we remain very sensitive to the cooling down. Especially as it pertains to media spend, I think the cooling off will hurt a number of companies who rode the wave up.
