“Data is the Oil, some say Gold, of the 21st century,” said Joe Kaeser, CEO of Siemens, at a 2018 tech forum in Stockholm. He believes ‘data’ is the raw material that our economies are increasingly being built on.
Taking the analogy further, successful companies use this raw material in its refined form – Business Intelligence / Consumer Insights – for making their business decisions.
Business Intelligence, based on consumer insights, is now enabling managers to better understand the dynamics of their business to anticipate change and manage risks. Avoiding the inherent risk in going by ‘intuition’, companies are embracing the systematic reasoning of insights to make decisions that are efficient, effective, and most importantly profitable.
From using Big Data, which is essentially using granular data to personalise products and services, to scaling digital platforms to match buyers and sellers, companies have started leveraging the power of insights. Recent research shows that insights-centred organisations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result.
A McKinsey survey revealed that even though the usage of insights is still relatively undervalued, its impact on business results is massive. Businesses that report extensive use of insights, in comparison to their competition, are
Without a doubt these are astonishing numbers, but companies need to embrace insights into their corporate ethos to reap the benefits. However, an alarming number of businesses are yet to acknowledge the potential. According to a recent Forbes survey, 87% of executives are not confident that they’re leveraging all available customer data.
Intrigued managers can take a cue from an industry that has historically embraced the value of insights – FMCGs. It is not surprising that FMCGs are the largest buyers of consumer insights in the market research industry. Consumer insight is at the core of their entire business cycle.
Product Development: Understanding the need of the consumer before developing the product, based on the insights gained from ‘Product Tests’. You have probably heard of Amazon Fresh and Whole Foods. This is a perfect example of how big data can help improve innovation and product development. The data-driven logistics gives Amazon the required expertise to enable creation and achievement of greater value. Amazon Whole foods are able to understand how customers buy groceries and how suppliers interact with the grocer. This data gives insights whenever there is need to implement further changes.
Communication: Ensuring that the intended message is getting across to the consumer by ‘pre-testing’ the advertisement and fine tuning it based on the consumer feedback. Netflix is a good example of a big brand that uses big data analytics for targeted advertising. With over 100 million subscribers, the company collects huge data, which is the key to achieving the industry status Netflix boosts. If you are a subscriber, you are familiar to how they send suggestions of the next movie you should watch. Basically, this is done using your past search and watch data. This data is used to give them insights on what interests the subscriber most.
Marketing: Measuring the brand’s performance using ‘Brand Tracks’ and enhancing the consumer experience of the brand through periodic marketing interventions. A real example of a company that uses big data analytics to drive customer retention is Coca-Cola. In the year 2015, Coca-Cola managed to strengthen its data strategy by building a digital-led loyalty program.
Customer Relationship: Keeping abreast with the market through ‘consumer connects’ and timely addressal of their grievances gauged through ‘C-Sat’ surveys. UOB Bank from Singapore is an example of a brand that uses big data to drive customer relationship and risk management. Being a financial institution, there is huge potential for incurring losses if risk management is not well thought of. UOB bank recently tested a risk management system that is based on big data. The big data risk management system enables the bank to reduce the calculation time of the value at risk.
Other industries too use insights in myriad ways to gain competitive advantage.
Big Data: Department stores analyse records of past purchases of consumers across various seasons to decide what merchandise to stock. Insights aid in predicting what will happen, instead of waiting for it to happen. These businesses gain competitive advantage by anticipating demand, maintaining inventory, and thereby creating profit.
Consumer Profiling: Retail banks ‘score’ their customers to predict the likelihood of an existing customer to be interested in purchasing another product from its product portfolio. As a result, they increase the number of products / services availed by the customer from the bank. Insights help them in reducing the overall cost of customer acquisition, which is a significant benefit to a retail bank.
Route to Market: Automobile brands conduct car clinics to gauge customer experience and enhance the product features before launching it in the market. Insights also help them to better profile the consumer and decide on the best route to market, For instance, they should focus more on exhibitions to display their product or dealers to promote their cars.
And not just data, competitive advantage can often be arrived at from Insights that are not generated from data in its conventional sense, but from observation. Customer-centric businesses are increasingly seeking more meaningful ways to gather consumer insights apart from the traditional research methodologies.
NBFCs have started mandating members of the executive team that they have a direct, and regular, contact with their customers. This interaction needs to be documented and reported during strategy meetings, as observations or key lessons learnt during interacting with the customers.
Other approach is for managers to spend an entire day in a supermarket or retail store to witness first-hand how customers interact with their products and the process of buying. This enables them to truly understand the ‘customer experience’.
Simply put, if you have a consumer, there exists a consumer insight that can be leveraged. Nevertheless, for the insights to deliver genuine value, it must be accurate as well as relevant.
Collecting, extracting, formatting, and analysing insights were once a delayed process. But today, with the advent of Big Data and Development of Business intelligence software, it has become easier to empower users without extensive technical expertise to analyse as well as extract insights from their data. As a result, less IT support is required to produce reports, trends, visualisations, and insights that facilitate the data decision-making process.
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