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The effects of the global pandemic have put marketing teams, like most business functions, under pressure to cut costs and deliver more. The martech stack, which takes the highest share of marketing spends (26.2% according to the Gartner CMO Spend Survey 2020-2021), has over the years witnessed unseemly bloat, and will likely be one of the first areas to be slimmed to drive efficiencies and cut redundancies. While many factors may have added to the bloat — marketers scrambling to deal with the omni-channel reality, the D2C onslaught from start-up challengers and disruptions that suddenly drove everyone online — digital marketing itself continues to grow and the urgency for a rational, responsive, CX-first stack isn't going anywhere.

Marketers are refocusing to deliver customer experiences that drive retention and revenue. Rebuilding or reorganizing martech stacks to facilitate the smooth flow, access, interpretation and activation of data for the next era of experience-led, ROI-focused marketing will be central to this effort.

Marketers Lean on Analytics in Good Times and Bad

In 2018, CMOs said their spend on marketing analytics as a share of overall marketing would rise by 200% over the next three years. A 2020 poll by West Monroe found nearly 60% of respondents had invested in data and analytics solutions in the preceding six months. "I’m not surprised that investment levels for analytics and intelligence remain at pre-pandemic levels," said Anita Brearton, founder of CabinetM, a martech stack management and discovery solution. "First, as companies freeze or reduce marketing spend, they are increasing revenue targets, which creates the 'do more with less' challenge. Second, CMOs need insights to optimize marketing performance and stay aligned with [pandemic-induced] changes in customer behavior. All that requires data, and data requires analytics to be understood and acted upon."

While marketers understand the importance of supply chain logistics, information value chain logistics are just as important, said Hemant Warudkar, CEO of Express Analytics, a marketing analytics solutions provider with multiple clients in the retail space. "Companies have to optimize their information value chain by connecting the dots, following the breadcrumbs, and nurturing the diverse referral sources." But with “multiple channels, deliberately obfuscated identities, multiple devices, scores of browsers, dynamic pricing and regulatory regimes," he added, "achieving incremental revenue while holding the line on [digital marketing] spend needs the strategy to be data-driven and based on advanced analytical capabilities."

The changing regulatory landscape is also driving organizations to value first-party data more than ever, said Steve Petersen, marketing technologist at Western Governors University. Adding to this is the movement away from cookies by tech behemoths like Apple and Google, and first-party data becomes even more valuable. As that happens, he said, “marketers need tools to orchestrate their marketing tactics with even more precision. That’s one reason why analytical tools are faring so well.” 

John Wall, partner at Trust Insights, an AI-focused analytics company that also runs the popular ‘Analytics for Marketers’ Slack Community, likens the CX stack to a fleet of vehicles. "You can go all the way down to an electric scooter and all the way up to a utility vehicle that can drive in any conditions, but without some kind of GPS (analytics) you’re not going to be able to tell where you are or go where you want to."

Related Article: Cutting Back on the DX Stack Fat

But Remember, Analytics Software Isn't a Cure-All

While analytics and customer data management will undoubtedly remain critical to modern marketing, marketers often have a hard time using it and/or driving returns from it. Challenges remain with finding the right solution and having the right skill sets in-house to drive quicker actions and lower dependence on IT. So how can marketers ensure their continued investments in data and analytics pay off?

Analytics is the practice of unlocking value from your data, primarily for the purposes of decision-making (for the business, campaign or tactic) — not the other way round (looking at the data and trying to make a decision based on it), noted Christopher Penn, founder and chief data scientist at Trust Insights. “It’s here that most analytics practices really fall down. An analysis is not a decision — it may inform a decision, and in the most advanced systems may trigger an automated decision — but it’s not a decision by itself. This is why analytics doesn’t pay off for many companies. There’s absolutely a place for exploratory data analysis, to learn what you don’t know, but when it comes to creating value with analytics, the decisions you need to make come first, and everything else is wired in to support that decisioning capability.”

Brian Piper, director of content strategy and assessment, University of Rochester added, “It's critical to understand strategic priorities and specific analytics needs before selecting products to add to the martech/CX stack. A piece of software won't solve your marketing problems but the right piece of software can provide you with the analytics you need in order to make the strategic changes to improve your marketing performance.”

The real value of analytics will come from solutions that go beyond what happened, to tell us “why something happened or what we should do about it” said Penn. “No system right now does a really good job of answering that."  

Related Article: How to Build a Successful Data Analytics Team

What's Next for Marketing Analytics?

Perhaps that’s where the next wave of AI/ML-led analytics tools will make an impact. My feeling is that the martech stack will organically move into two buckets — automation and intelligence tools. Marketers will seek more efficiency with the automation of tasks and more effectiveness with on-the-go intelligence that enables a deeper understanding of customers as they journey across channels, devices and platforms making their buying decisions.

Either way, data, analytics and customer data management tools will remain central to these evolved CX-first, ROI-focused martech stacks. The challenge — and opportunity — will lie in how well marketers are able to use them.