Recent business press articles about marketing, data and analytics quickly give us a feeling that in 2021 we will witness a sharp increase in companies’ investments in data and analytics to improve marketing decision-making. For instance, last Thursday 3M said that despite a series of serious cuts it needs to implement to deal with the impact of the COVID-19 pandemic, in 2021 3M will “step up the use of analytics and data to improve efficiency and enhance marketing in response to an increasingly digital age” [link]. In fact, marketing analytics are already growing at a fast pace, with analyst reports predicting that the market – valued at USD 3 billion in 2019 – is projected to more than double in the next seven years, reaching nearly USD 7 billion by 2027 [link]. Along similar lines, in a recent CMO survey conducted by Gartner, many CMOs rank marketing analytics as their second highest investment priority (after brand strategy), and 73% of CMOs stated they planned to increase their investments in 2021 [link].
However, there are also important challenges to be wary of when thinking of investing (more) in marketing analytics. For instance, many senior marketers (i.e., CMOs and VPs of marketing) remain unimpressed by the results of recent marketing analytics investments, with 54% of senior marketers indicating that marketing analytics did not yet have the influence they expected [link].
We identified the following four key challenges that, if not adequately considered, may hamper the growth and impact that marketing data and analytics can have in an organization:
The challenge we hear most often regarding marketing analytics relates to the lack of integration between the efforts made by data and analytics teams and the concerns and goals of business decision-makers. Analyses and data gathering efforts that are disjointed from the concerns and goals of senior business decision-makers prevent decision-makers from leveraging the best of two worlds: data-driven analyses combined with insights derived from strong business acumen. Faced with such disconnect, decision-makers may often go with their gut, potentially defeating the purpose of the analytics teams' efforts. We thus need to make sure that data and analytics teams communicate seamlessly with business decision-makers to ensure that analytics efforts are guided by clear business goals, questions , and context.
Analytics are deployed but not used
Even when analytics are already in place and are a good match with business decision-makers' goals, they may not be sufficiently used in decision-making. For example, Gartner’s 2019 Market Insights Business Partner Survey shows that despite recent investments in analytics only 52% of business partners surveyed stated they use data and analytics to make marketing decisions [link]. Companies may thus need to also ensure they stimulate buy-in for analytics among key users of such analyses and insights (e.g., marketing decision-makers).
Another possible reason for lack of impact of data and analytics on business decisions may be, ironically, that in some cases marketers may have too much data and analytics at their fingertips, possibly leading to data overload. For example, in a 2018 HBR article Carl Mela and Christine Moorman argued that too much data creates important bottlenecks such as lack of integration between systems, high processing and analyses costs, and reduced agility and speed when trying to connect voluminous sets of data and analyses to extract insights [link].
A related challenge is the tendency - especially of analytics savvy teams - to opt for the latest and most complex algorithm even when simpler approaches would be leaner and equally effective. For instance, Neil Hoyne, chief measurement strategist at Google, recently said that “the companies that are going to win are the ones who are using data, not guessing”, yet, he also cautioned that it is important to match the right analyses to the decision at hand. In the same article, Raghuram Iyengar, director of the Wharton Customer Analytics center, goes one step further suggesting that savvy marketers go always for "simple, first". He recommends analytics teams and marketers to always ask the question "is a complex analysis really needed to solve this problem?” because often you “don’t need a bazooka to get a fly.” [link]
In sum, marketing analytics are here to stay but we need to gain maturity in the types of analytics solutions we design and implement, and how and when we use them. The key is to ensure a seamless integration between the analytics solutions we design and implement, and the business goals they should be serving. We believe this objective should become a top concern of marketing leaders in 2021 and beyond. To read more on how to address this challenge, take a look at our recent post on our analytics growth flow process.