Using big data to improve the customer experience

Big data is rapidly emerging as an important resource for enhancing customer relationships. Teamed with predictive analytics tools, it can be used to improve loyalty, increase sales opportunities and boost the bottom line.

Today, finding raw data to work with shouldn't be a problem. These days there is a proliferation of customer-experience channels generating vast amounts of data. Every call to the contact centre, every service request, every visitor to your website and every time a product is shipped contributes to the store of available data. The difficult part is bringing all this data together in a way that facilitates analysis. This is where big data comes in.

Big data is a relatively new concept and there are many definitions. However, big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Used in real time, such information can provide competitive advantages over rival organisations and result in significantly improved customer experience leading to increased revenue.

While storing all this data is relatively straightforward, extracting value from it is another thing entirely. There's little point in collecting terabytes of data if it can't be used to add value to business activities. On this front, significant progress is being made. Powerful predictive analytics tools can be used that scour large volumes of data and spot trends and inter-relationships that would previously have gone unnoticed.

These tools can analyse existing data stores while also monitoring real-time data as it is captured. That way historical customer activity can be compared with current data, allowing changes in demand to be quickly identified.

Those businesses that grasp this opportunity will find they have a significant competitive advantage: better insight into what their customers are seeking, together with new perspectives on macro trends that could shape the market in coming years. Businesses that position themselves to take advantage of these opportunities will find themselves better able to predict trends and issues before they emerge, thereby ensuring they are best placed to match their offerings with proven customer and market demands.

Armed with big data and predictive analytic tools, businesses can align themselves more closely with their customers in a range of ways, including:

• New products and services - based on insights into shifting demands, businesses can change their product mix to ensure it is better aligned with real-world customer requirements. Older products can be retired and resources focused on those most likely to succeed.
• Upselling - having a clearer vision of the products and services a customer has purchased in the past allows a business to proactively offer new products more likely to suit their requirements.
• Better communication - rather than broadcasting marketing messages using a 'one-size-fits-all' approach, campaigns can be tailored to an audience of one.
• Personalised experiences - based on information gathered and analysed from previous interactions, future interactions can be personalised and streamlined. Customers will no longer be treated as an 'unknown' person every time they contact the business.
• Omni-channel interaction - regardless of how a customer chooses to interact with a business - through a bricks and mortar store, a call centre, online or via a mobile device - the experience can be consistent, ensuring relationships remain strong.

As a further step, internally collected customer data can be combined with data from other external sources. This data might come from social networks, governments (economic data), research companies and other businesses active in the same sector.

Using predictive analytics tools, these massive sources of data can be analysed to uncover macro trends that may have an impact on future business performance. For example, demographic data can provide insight into where new stores should be situated or how a product line should be overhauled to cater for changing social tastes.

In the near future, even more data will be generated by machine-to-machine interactions. These will include everything from product manufacturing lines and supply chains to sensor networks. Such rich data will provide the opportunity to extract greater insights into customer behaviour, trends, supply chain and logistics that can further enhance business planning and execution.

For the businesses that use big data and predictive analytics in this way, the opportunities are vast. Fresh insights can be gained that can shape everything from manufacturing and stock selection to marketing and advertising campaigns.

Ananth Siva is Managing Director - Asia-Pacific at [24]7