In COVID-19 times, having access to consumer data is no longer a problem for manufacturers. What differentiates companies these days is really the power to perform the necessary analysis and generate valuable insights. How exactly do we generate consumer insights in an era of data 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 to understand 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 contributing 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 on 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. 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. It’s time to get a System of Intelligence to work for you and help you move from Data Overload to Consumer Insights.

The Birdie Solution

Consumer insights

At Birdie, we collect and analyze competitive consumer data from the main e-commerce platforms, such as Amazon, and deliver it to you as a set of actionable insights ready for your operations – and we connect it to other data sources to make the analysis complete. In other words, we give you all the insights and you take it from there.

Think about the typical consumer review. It will likely mention the product, features of that product, positive or negative qualities or sentiment, and something about who the consumer is, such as gender, marital status, profession, and possibly much more. Now imagine millions and millions of reviews talking about different products, including your brand and your direct competitors. How valuable can it be to see all this information in one place, to be ahead of the curve and take action while others are still figuring out how many reviews they have, or are satisfied in counting review stars?

How will you position yourself as a company in face of this direct contact with your entire consumer base? That’s exactly what we can help you with.

Feedback Analytics Platform for a better product strategy

Birdie helps product-centric companies better understand customers at scale to create product strategies to increase acquisition, conversion, and retention.

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