You are currently viewing How data-driven insights can fuel a new level of customer centricity

How data-driven insights can fuel a new level of customer centricity

What makes a company a successful digital disruptor? A technology-driven view of the customer that enables excellent service and insights is a great starting point.

Digital disruptors have a great handle on their customers and, in fact, a modern business needs to be data-driven to really succeed in today’s online economy. The challenge is capturing the right data to generate insights and many companies still have data scattered widely across different systems.

Discovering the potential of data

To realise how data can improve customer service and open new opportunities, start by assessing how data and analytics can be the “fuel” for a number of initiatives across your business.

Such data-driven insights might include:

Marketing: Track the effectiveness of marketing campaigns, including direct-to-customer and through partners.

Sales: Find out what your customers are buying, not buying, and why. Metrics like cost, quality, brand equity and fit-for-purpose are all important here.

Operations: Get meaningful insights from your business metrics, such as sales, delivery, production and consumption.

Channels and supply chains: Understand the effectiveness of your channels and supply chains – is a product worth the wholesale margin cost?

Customer profiles: Get insights into what else your customers might like to buy and what services they are buying already.

Once you have a good handle on the potential of data for customer service you can begin developing a strategy for managing and processing the data to deliver better insights to the business.

Data capture and analysis

When building a new data analytics function, a holistic view of how the company’s data is being generated and, from there, how it can be processed, is essential.

Considerations when building a data analytics function include:

Capture: How and where will your data be captured and stored as more processes go digital?

Access: Will the data about your customers, suppliers, business be held within your business, or trapped in a proprietary system? Data access is crucial if you are going to be acting on it. For example, using commercial SaaS applications in yourbusiness can see data locked up in their systems, or hard to extract for your needs.

Security: Like access, it is important to know how your data is secured, “who” (including machines) has access to it and how is it transmitted. If you are possibly handling personally identifiable information (PII) security is a must; as is compliance with the Privacy Act.

Visualisation: Some of the best decisions are made when people can literally see the insights. What are the meaningful ways you can visualise the data? Often, a Data Abstraction Layer (DAL) is the enabler – sometimes called a ‘data lake’ – or, if you’re small, ‘data puddle’! This keeps the process of data gathering and processing separate from analysing and visualising, and makes te- chnology choices within each interchangeable.

Repository: Data-driven businesses will amass more and more data. Do the various systems you use have access to (read and write) your data store? Is the data store large enough, secure enough, and backed up? Will it be available in the event of a disaster, to rebuild from?

Consumption: How will your data be consumed and will the right people be able to act on it appropriately? Do you need a self-service function so dashboards and visualisations can be created by those who will consume them?

Getting a handle on data management and analytics now will save a world of problems as you grow.

Next steps with machine learning

An interesting development is AI and machine learning, which can go a long way towards automating and streamlining common process pain points.

Going the next step with customer centricity means applying machine learning and AI to your data to get insights. This is a really specialised field, but the insights and predictive analytics can be powerful; larger datasets are needed for success here, but these could be a combination of your own data with anonymised data from your sector, vertical or region.

Fundamentally, data, analytics and AI can be the engine room for your digital company. They will let you understand your customers and business metrics now, see how they change with each initiative, and sound the alarm early if

– Anthony Woodward is founder and Chief Executive Officer of Accelera