Using data to figure out customers

Aditya Rath | Updated on March 05, 2018

With fresher perspectives and parameters, marketers can mine a wealth of information and home in on what will appeal to buyers

Data is fuelling everything lately. In the quest for growth, competitive advantage and efficiencies, organisations today are altering the way they cull business intelligence from data they have on customers and the markets in which they transact. This in turn has also changed customer behaviour and expectations.

So what has changed?

Below are the key developments that have changed customer behaviour and expectations.

Democratisation of information: In a world of information abundance, customers today can rely on a wide variety of influences when making buying decisions.

Lifestyle the lifeline: Connectivity 24/7 has affected how we live and work but attracting and retaining your consumer’s attention is getting harder day by day.

Rise of personalisation: Today, technology is increasingly reducing a market’s cost of entry. This is due to the fact that there are multiple business models, services and products available to customers by way of an endless virtual aisle.

So how does one respond and cater to the demands of today’s customers?

Catering to today’s customers requires a specialised and granular understanding of their needs and wants. By developing a detailed understanding of the customer’s ‘Five Mys’ – my motivation, my attention, my connection, my watch and my wallet – at multiple points in their life, companies today can identify how, where and when to engage them. Understanding the trade-offs customers make during the day can provide much intelligence. As an example, a person may have a tight budget on grocery but may splurge on shoes.

Getting a clear understanding of how consumers view these trade-offs requires new forms of data and research to generate the right depth of insight. With abundant data available more than ever, this insight should be guided by four key principles:

Customer level: Understanding and grouping insights at a segment level is relevant and important, but it’s often most valuable to generate them at the lowest level of granularity that can be actioned.

Dynamic: Monitoring and assessing individual customers’ preferences as they change over time and throughout categories is critically important as well. Yet this effort must be balanced with enough stability for the organisation to make decisions.

Being multidimensional: There are many factors that go into purchase decisions, thus relying on one core attribute in today’s market can be dangerous. Similarly, assuming that all consumers who value product quality also have a certain price they are willing to pay is a fallacy. These are dynamic and interrelated decisions. Therefore, thinking of your customers as having an underlying ‘DNA’ of preferences rather than simply bucketing them into one ‘need state’ is imperative.

Scaled: It was once acceptable to research a representative sample of customers and use it to predict the attitudes of the whole. Still a common technique, manufacturers and retailers should constantly re-examine if a data set is available that would make the same basic insight more granular and actionable. For instance, while it’s still valid to ask consumers how important time savings are to them, it may be more scalable and actionable to measure the drive time from their home to a store. New data sets are constantly becoming available to make this analysis more achievable.

Putting it all into practice

Often these ideas resonate with brand marketers, but the challenge lies in acquiring the data and capabilities to put them into practice. KPMG International’s research found that nearly 56 per cent of the people are ‘concerned’ or ‘extremely concerned’ about the way a company handles their data.

Organisations today should take decisions and identify levers that can be pulled by their brand, and then work backwards to the best source of data and insight. Before that, however, organisations should ensure they challenge the thinking on the levers that can be pulled. Historically, brand marketers may have thought, for example, that they could only influence packaging at the shelf. But with new technologies and innovations, many more possibilities are available and are often overlooked out of habit.

Once organisations are clear how to action more granular data, sourcing it among many options will require some creativity. They should look at buying data, partner with a firm or simply use the extensive public data available to the best of their advantage. The right option will depend on the organisation’s end-execution needs, time frame and budget.

Lastly, an organisation’s decision-makers need to understand and buy into the need for data and perceive how it can improve decision-making. After that, incentive changes, new processes and tools and training can help enable your colleagues operate in a different way.

Aditya Rath is Partner, Management Consulting, KPMG in India. Dev Khandwala, Manager, KPMG in India contributed to the piece.

Published on March 05, 2018

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