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The events of spring 2020 have turned marketers’ worlds upside down. In light of an unprecedented health and economic crisis, teams scrambled to adjust their advertising messages, campaigns, and offers. They could no longer rely on previous assumptions about their customers, including what, why, and how they buy. In a matter of days, stores closed, e-commerce sales ramped up, and contact center interactions exploded. Meanwhile, media consumption changed as more people began working from home, spending more time online and watching TV, and less time interacting in person.
Rapid change is the new normal, and more than ever, marketers need to make decisions quickly that are nonetheless anchored in data. As a result, companies are pouring money into marketing analytics — last year, CMOs invested more in this category than any other, according to Gartner. Yet, even as marketers bury themselves in data, they are getting an incomplete picture of performance and their customers. Below are four approaches that marketing teams should be using more often to better orient themselves around the truth of what their customers are experiencing and which strategies are actually working.
Earn the Right to Use More Data
Too often, marketers invest countless hours collecting a sea of data without a clear strategy for harnessing that data to drive decisions. That leads to mental fatigue and a tendency to revert to assumption-based decision-making. Our research has found that nearly a third (31%) of marketers say they face the challenge of “too much data to analyze” when optimizing ad performance. They’re swamped.
To get back on track, start with the simplest dataset needed to make an informed business decision and build a virtuous feedback loop between data, insight, and action. Attribution modeling is a good example. It is often difficult to get the resources required to build a proper attribution model, so I advise marketers to start small, prove business impact with smaller wins, and then make a stronger case for integrating new data sources.
Redefine “Digital” Data
The definition of digital is expanding, and marketers’ understanding of digital data should, too. While consumers still click on Google results and scroll through Instagram, they also email, call, text, and chat with brands. During uncertain times, in particular, consumers value direct communication. In the wake of Covid-19, many marketers pulled back on campaigns and canceled events, focusing instead on communicating with their customers and building community.
Whether customer interactions happen online, offline, on mobile, or all of the above, they generate digital data. Internet of Things (IoT) platforms are giving companies visibility into how their services are used — whether it is data about internet usage (in the case of a telecom provider) or total miles driven (for an insurance carrier). These usage patterns can help businesses understand if customers are using the services for which they are paying and getting the appropriate value. Contact center conversations and in-store visits are also being “digitized” and represent point-of-sale insights into buying behavior.
Now, it’s possible to measure behavior that used to be impossible to track. In-store purchases and phone conversations with customers were once regarded as an “offline” data black hole, as there was no way to accurately track and attribute sales to previous online behavior or marketing and advertising efforts. Marketing technology has evolved, however, and this offline data is now digital, which means it should be analyzed like any other online activity. For many businesses, this data is critical to decision-making, especially as competitive, customer, and market realities quickly evolve.
Identify New Moments of Truth
In 2011, Google coined the term Zero Moment of Truth, which is a customer’s first step in researching a product or service to buy. Today, there are countless micro-moments involved in the digital path to purchase, and the most significant moments of truth may not be what marketers expect.
Consider the example of a smart home device company that sells a number of different products online. A customer might search for “home security systems” and click through to a security camera landing page, then navigate around the site and end up buying a smart lock. The key moment of truth is the landing page for a different product; it shapes the customer’s impression of the brand and encourages them to take the next action.
The moments in the buying process that influence the customer’s decision to purchase, and in turn influence revenue, should be analyzed, A/B tested, and optimized.
Connect Analytics to Revenue Generation
Marketing analytics should shed light on the interactions that drive revenue — not just those that are easy to measure. Phone conversations are an untapped source of insight, particularly in categories like finance, healthcare, and telecoms (which sell products and services that are complex, emotionally fraught, and at a high price point).
One of our customers, DISH Network, sells TV packages and does a significant portion of its business over the phone. For DISH, calls convert at a higher rate than online interactions — half of its new subscribers talk to a representative on the phone before buying a package. The marketing team prioritizes conversational analytics, connecting call center and paid search data to target more high-value prospects. As a result of these efforts, DISH has improved its conversion rate by 60%.
While it may be easier to measure and optimize email open-rates or website visits, marketers need insight into the conversations that are converting to sales. That means analyzing phone calls the same way as any other digital activity.
In today’s uncertain economic and public health environment, it is more important than ever before to make decisions that are grounded in facts and connected to revenue. Effective use of data and analytics can help marketers stay anchored to their customers’ changing reality and focused on their moments of truth.