With more than 79% of respondents from larger companies (500 people +) indicating that both automation and big data analysis, including synthesis of multiple data types, are game changers or interesting trends, these techniques have taken center stage in our industry. Automation has been applied in tactical areas like concept, copy, and claims testing, allowing brands to sort through opportunities faster and more affordably, quickly killing bad ideas to focus on the good. While the use of big data and multiple data types hasn’t been fully utilized yet, it’s certainly picking up steam in the industry when it comes to obtaining and applying deeper, more holistic insights to gain a competitive advantage. The true opportunity brands now have is in combining these two techniques in an agile way and applying them to audience intelligence upstream in the innovation process.
Brands know the path to growth is through innovation. More than 75% of respondents from large companies are focused on their company’s growth strategy; more specifically, insights buyers have top priorities of delivering recommendations that answer business objectives (74%) and help grow their business (66%). So how can brands innovate and get better at creating strategies to drive even more success? By connecting these two seemingly disparate game changers—automation and big data—to better identify and understand their most profitable audiences upstream in an agile, actionable way. This enables the right audience-centric decisions that quickly lead to successful innovations that help grow their business.
Traditionally, audience insights have been incomplete and limited to what a survey or qualitative study can do, and the methods are slow and expensive. Traditional audience intelligence is where concept and copy testing were six years ago before automation. Moving and iterating quickly in the front end of the innovation process leads to agile audience intelligence, the key to competing with disruptive brands that steal share—like Dollar Shave Club, who identified a highly sought-after market niche, put that audience at the center of everything, and used modern marketing to activate against that audience. This allowed them to scale from $0 to $200M in revenue in five years before being acquired by Unilever for $1B. Traditional audience understanding is ill-equipped to drive the real-time, specific insights needed to compete in today’s dynamic market.
By using a connected data approach (fusing survey and behavioral data), there are a number of ways to identify and understand audiences quickly and affordably. For example, to capitalize on their most profitable group of customers, one of our clients in the tech space needed to identify and profile an early adopter audience within their segmentation. They combined survey and big data to identify and understand this sub-segment. The combined data allowed them to determine the size of the prize; pinpoint the features that warranted focus during development; understand how to apply this audience’s personality insights to communicate effectively; and determine which digital attributes and which channels to activate against for optimal reach. These insights were gathered in a couple of weeks for the cost of a couple of focus groups.
By adopting modern solutions that bring agility to audience understanding—upstream in the innovation process—brands can accelerate time to market and compete in a smarter way using multi-layered insights that enable them to take a more personalized, effective approach leading to successful consumer-based strategies. The next frontier of agile is about building audiences and agility up front and applying this rational connection to each stage of development to win. Enabled by big data and automation, we get agile audience intelligence to drive growth at scale through innovation.
To see an example of how one tech company used a solution that increased their audience intelligence during product innovation, take a look at this infographic.