There is truly no better experience, as a customer than walking into a favorite coffee shop or diner and being greeted by name by a proprietor that already knows what a loyal shopper is likely looking for. In the digital age, the marketing equivalent of know a customer’s “usual” is not just collecting data, but thoughtfully using that market intelligence data to make each member of a brand’s audience feel as though they are seen and valued. And as data-driven marketing technology gets better and better, that level of personalization is becoming required for any business looking to stand out in a digital sea of sameness.
In fact, the recent Gaps in Customer Experience Harris Poll found that “53% of consumers surveyed said that they expect a brand to know their buying habits and preferences and should be able to anticipate their needs. Further, 37% said they would stop doing business with a company that doesn’t offer a personalized experience. The fluid, omnichannel buying journey is here, and unless a brand shows a customer that it cares about them along every mile of a dynamic journey, the customer may have switched brands by the time that all-important last mile comes into play.”
What Are Market Intelligence Data Sources?
Market intelligence data sources are the key datasets marketers use to make data-driven purchasing decisions. This can include customer behaviours and insights, marketing data and other industry specific analytics.
Market intelligence data: 10 types to know
In the Skai report, Mind the Data Gap, learn about the evolving, highly competitive CPG landscape and why data is the key to unlocking performance in this new age.
This complimentary report breaks down why brands need the right data in order to optimize marketing programs, identify valuable emerging trends, and build products that are the best fit for the market. In today’s complex market, the only way to navigate forward is using a data-driven approach—and in this approach, your decisions are only as good as the data you have on hand at the time.
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The following are ten key types of marketing intelligence data presented in that report which brands simply can’t afford to overlook.
While there are other, perhaps more complex insights to be gleaned from online behavior, starting with the basics is never a bad idea. To get a full picture of an audience as a whole, it’s crucial to know who the audience is individually by gathering demographic data such as age, gender, and household income. Understanding these small but key bits of information, like household size and income, is a critical first step to creating a complete data picture.
And along with that important demographic data, understanding where buyers are in terms of life stage is also a crucial building block. Are customers married, single, or engaged? Are they homeowners? Are they likely to be homeowners or parents soon? Marketing to first-time homebuyers is quite different than selling to retirees, so getting this glimpse into day-to-day life will be valuable for starting conversations with potential customers.
Some of the best data available to marketers come from the way existing customers interact with the brand. Collecting information about which items are languishing in shopping carts, which items were browsed, and which items made it all the way to the purchase stage provides some of the best data available for what actions might make a first-time customer a lifelong customer.
But learning about customers who have yet to make a purchase based on signals such as the content they’re consuming, interests they’ve expressed through channels such as social media, and even the types of apps they’re downloading are also important datasets for marketers looking to engage new audiences.
Marketers often pay close attention to customer behavior onsite and via social but forget a critical part of this data: how customers are engaging. Gathering information not just around which devices a customer is using to access information but how long they’re spending with each of those devices, along with the kinds of content they’re consuming (such as video versus text) provides critical context for which methods of communication target audiences might respond to best.
Of all the engagement data available to marketers, perhaps the most helpful is also the most basic. Those clicks, likes, shares, and email opens (or lack thereof) are pretty much the best and most easily accessible data there is around what customers want and expect from a brand.
And beyond clicks and opens, the ways audiences navigate a brand’s website also provide key data around what is working and what should be worked on. Paying careful attention to users’ path through a website, from page views, content engagement, and external links followed, helps marketers literally walk a mile in visitors’ virtual shoes, tracing exactly the ways audiences are consuming a site and then making that path a little more clear.
Keyword data derived from paid search is a valuable way to strengthen future campaigns and course-correct existing endeavors, but it’s also a strong indicator of what specific audiences are looking for from a brand. These insights help to generate not just the most efficient traffic, but also the most effective traffic.
Applying audience targeting data, such as CRM data, lookalike, and retargeting, to media platforms means creating a complete picture of the respective value of each dataset. Understanding this data is also critical to not only which bids will have real value but also which pieces of creative messaging are resonating with each of a brand’s audience segments.
It can be easy to miss the forest, in this case, what audiences truly want from a brand, for the trees (our short-term goals for individual campaigns). Brand study data around sentiment, ad recall, purchase intent, and brand affinity helps to create a more holistic picture of how all of a brand’s marketing and advertising efforts are working together to push a cohesive message. There’s power in unity!
For more marketing intelligence data insights, read Skai’s report “Mind the (Data) Gap: What CPGs Need for Retail-intelligent Advertising and Ecommerce Success” here.
\Read this report to learn more about:
- The new market shifts creating the challenges facing today’s consumer packaged goods marketers
- Why consumer data is the key to overcoming ecommerce obstacles
- The types of market intelligence data CPG marketers lack and why they need it
- How to access and activate critical datasets
- Recommendations for building a CPG marketing practice based on data