Four ways that data science can boost the customer experience

Monday, 16 August 2021 02:10

Four ways that data science can boost the customer experience

Chris Tucker, Vice President – Australia and New Zealand, HCL Technologies

What is Data Science?

GUEST OPINION by Chris Tucker, Vice President – Australia and New Zealand, HCL Technologies:  Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data and apply knowledge and actionable insights from data across a broad range of domains. It’s certainly a lot more than reports and analysis and it’s moving from the back room to the forefront of many businesses as it gives meaning to the numbers.

Keen to differentiate their offerings in a competitive market, increasing numbers of Australian firms are turning to data analysis as a means of improving the customer experience they offer. At the same time, public sector agencies such as the Australian Taxation Office are also deploying data analytics to provide greater community accountability and in its case to support tax payer compliance.

As a result of rapid advances in computer vision, machine learning, and artificial intelligence, businesses can leverage insights from structured and unstructured data in ways never before possible. Accurate pictures can be created of customers that identify needs, tastes, and likely decisions.

This allows tailored offerings to be created that closely match their requirements. Rather than having a single offering for all, customer experiences can be tailored to the individual.

However, despite the rapid rise in data volumes and analytic capabilities, many businesses continue to struggle in their attempts to scale their customer experience management capabilities. In fact, a McKinsey study discovered that only eight percent of firms are engaging in the core practices needed to support widespread adoption of data science.

To overcome this challenge, there are four ways in which businesses can make better use of data science to improve the customer experiences they offer. These ways are:

1. Overcome organisational barriers
Often, organisations can have the right technology, the right data, and the right analytic models in place, yet they still fail. In such cases, the failure of digital transformation is usually found in organisational structures and leadership.

The first step towards winning the customer experience game is winning over internal stakeholders. Organisations need to be trained from the top down to propagate the value of data science and the value it brings to the business. And, while traditionalists might still be hesitant, data leaders need to show that black-box decision making is a thing of the past as data-driven insights can enhance the contributions from across every level. This is a key step if an organisation wants to fully adopt data-driven automation.

2. Invest in forecasting and predictive analytics
Digital customers are accustomed to instant fulfilment and are increasingly used to receiving instant recommendations for items they actually want. By analysing customer demographics, product information, and customer purchase histories, businesses are able to design and deliver custom decision support services. These services can maximise inventory forecasting accuracy and ensure that the right products are available at the right time, at the right stores and at the right price.

3. Focus On hyper-personalization and real-time feedback
E-commerce is the home of hyper-personalisation, but brick-and-mortar stores can achieve a similar outcome. Some businesses are using image recognition technology to extract meaningful information from optical photo and video footage.

For example, this can allow a supermarket to collect and analyse real-world data using solutions such as Tableau and SAS that can help improve customer experiences. Customer movement in stores can be analysed to better understand the products viewed by customers, their dwell time, brand preferences, demographics, traffic flow and repeat visits.

Changes can then be made to factors such as store layouts to improve customer flow for more comfort and ease. Retailers can also optimise their inventory and shelf management to offer customer-centric placement and greater appeal. Immediate results can include higher footfalls, greater sales, and an increase in customer loyalty.

4. Enhance product quality
Nothing wins customers over more than getting exactly what they want. Making use of data to monitor supply chains and production quality can ensure the standard of products on offer is consistently high at all times.

If customers know what to expect, and receive it each time they visit a business, they are likely to remain loyal over an extended period.

A data-driven future

With the volume of data available to businesses constantly growing, opportunities to put it to work to improve customer experiences will continue to increase. Everything from previous interactions to demographic details can be used to tailor experience and make them more engaging.

Future companies will excel in the face of competition if they are able to use data analytics, such as Azure. Data-driven customer experience is a necessity for future success where businesses must be agile and collaborative with their solutions, sense change quickly and then confidently respond to it.

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