How to Effectively Obtain Consumer Insights in a Data Overload Era
Everybody knows how important is understanding your customer, but how to do that in an era of Information Overload?
The COVID-19 pandemic has brought numerous impacts to our routine. One of the most important factors organizations are discussing is the acceleration of Digital Transformation and its impact when it comes to data and technology. As noted by The Economist, one of the most obvious consequences of the pandemic will be “the infusion of data-enabled services into ever more aspects of life.” Which brings together another problem, the huge amount of data and how to get valuable consumer insights into that. Everybody knows how important is understanding your customer, but again, how to do that in an era of Information Overload?
What is Data Overload?
Information overload, a term coined by Debra Brass (former global president of J&J) in 2013, describes a reality in which the excessive availability of data makes its analysis so complex that, at a certain point, it becomes dysfunctional and stops to contribute to insightful analyses. It prevents companies from effective decision making because they can’t take action in face of so much data.
This problematic context is likely a result of the rapid evolution in a company’s ability to collect data, which is not followed by an evolution in the ability to integrate and analyze that data correctly. While the problem may affect companies as a whole, it is especially problematic for customer-facing teams such as Marketing, Customer Service, Sales, and Consumer Insights.
Several studies estimate that up to 80% of a Marketing or Consumer Insights executive’s time is spent trying to analyze consumer data. Among these executives, only 1 out of 5 believe they have the right tools for the job. The exponential increase in the number of customer reviews in e-commerce platforms is a good example. Consumers are not only writing more reviews but also asking and answering more questions online, generating challenging amounts of data to analyze.
This is as much of an opportunity as it is a problem: with more consumer reviews and conversations, companies have the chance to get access to that data and learn, in a very unbiased way, about their consumers, in real-time and faster than ever. But how can they explore a new source of consumer information when they are still struggling with data overload, and are not getting the insights they are looking for?
How to turn data into Consumer Insights
The answer is to make use of Systems of Intelligence. This concept, coined by Greylock Partners (one of the most relevant investment funds in the software industry), is for many seen as the next big wave of innovation in the world of data analytics. Systems of Intelligence appear as an additional layer that connects Systems of Record – platforms on which the data is stored, such as a CRM or ERP platform – and Systems of Engagement – platforms on which interactions occur to capture that data (such as a Customer Service or messaging tools).
The main value proposition of Systems of Intelligence is to connect different data from different sources – that in most cases are underutilized because companies can’t even access them – to make it possible to generate deep insights from these data. By implementing these systems of intelligence, companies can not only reduce their work of connecting their own data with spreadsheets but can also add new sources of data into their analyses in a much easier way, with less technical challenges and a streamlined workflow, improving their quality in every operational cycle.
Returning to today’s context, it is precisely a solution like this that seems to be missing. We all have access to data, but in most cases, we don’t know for sure what to look for: we analyze the wrong data, looking only at a part of the collected content without seeing the correlation of this with the rest, and we even chose the wrong metrics to measure it. More than that, we spend more time trying to understand the past than planning the future.
As a result, not only do we make the wrong decisions, but we also waste a lot of time focusing our energy on actions that are not relevant to our success. According to a Gartner’s Study, 60% of the areas of Data Intelligence and Consumer Insights will be cut by half by the year 2023 simply because they are unable to generate value from the captured data.
Marketing and Consumer Insights executives need to reduce the burden of spending hours on excel trying to process and connect several sources of data to – only maybe – get relevant insights.
The Future of Consumer Insights: Decision Intelligence
With “dirty data” costing the US economy $3.1 trillion a year and 2.5 quintillion bytes being generated every day, it’s not a surprise to say that the future of Consumer Insights has a direct relationship with Systems of Intelligence. The name? Decision Intelligence.
Decision Intelligence is a framework that helps with the operationalization of AI, ML, and Text Analytics for real business decisions, prioritizing the business and putting the technology to work for it. According to Gartner, by 2023 more than 33% of large organizations will have analysts practicing decision intelligence.
The reason why it’s so powerful is that it connects business goals, aspects, and questions to the power of Artificial Intelligence and Predictive Analytics working over several sources of data to develop foresight and anticipate the future.
Bio: Patrícia Osorio has more than 10 years of experience in marketing and business development. After graduating in Law from USP and Business Administration from FGV-EAESP, she joined Arizona in 2007 to lead the marketing department and was the responsible for product innovation and new markets development projects, such as internationalizing the company (selling to clients in Argentina, Chile, Colombia, and the UK and opening an office in Argentina) and developing digital products. She also co-founded HomeRefill, an online subscription e-commerce and GVAngels, an angel investment group that has already invested over 1 million dollars in Brazilian startups. Pat is a growth hacker graduated by Growth Tribe (Europe) and has experience with B2B Growth and Acquisition in Brazil and the USA. Together with Alex, she saw the opportunity to use product data for insights and drafted the first version of Birdie in late 2017.
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