How to generate greater ROI through consumer analytics

By  Tiffany Jayne Carpenter Head of Customer Intelligence Solutions UKI

The growing complexity of customer journeys, the deluge of big data, and shifts in the balance of power to consumers, means that if businesses are to connect and engage with customers, they need to be able to quicklystitch together online and offline customer insights to accurately predict their behaviour - and consumer analytics holds the key to doing so. 

Long have businesses understood the need to research the marketplace and their customers in order to understand and  predict buyer behaviour, utilising market research and transactional data to help make data-driven decisions.

However, as customers engage with businesses through a variety of channels - and the increasing dominance of digital - businesses need to understand each customer journey at a granular level to be able to drive positive business and customer outcomes both now and in the future.

Of course, achieving this level of insight is entirely possible through the use of consumer analytics - but while many businesses have solutions in place for capturing customer interactions and preferenes, the data is often spread across the enterprise and stored on legacy systems and siloed databases and channel specific solutions, making it difficult to get a single consolidated view of customer behaviour.

The fact is that businesses that leverage customer behavioural insights and consumer analytics perform considerably better than those that don’t. The value of such activity is clear. Businesses, armed with consumer analytics to drive customer intelligence are able to go beyond simple collation of the numbers and can start to deliver more personalised interactions across every touchpoint in the customer journey, crafting compelling customer
experiences and knowing just when to engage.

Integrated into the business' strategy correctly, consumer analytics can help to map out customer journeys based on quality data to deliver the best customer experience possible and maximise business return on investment (ROI).

Points for expansion

  • What are the challenges for businesses ahead of utilising consumer analytics?
    • Managing large volumes of data: some businesses have legacy systems and siloed databases across the organisation. While this data is useful, it needs to be moved to a central database for analysis if they are to get value from it. 
    • Data collection: Some businesses do not capture data at every stage of the customer journey, subsequently leading to inconsistency. Of course, much of this is down to the complexity of the digital landscape (omnichannel) and being able to capture the data across these channels properly to attain in-depth customer insight. Businesses need to put greater emphasis on harnessing a single customer view and pooling data into a centralised platform. Often the data capture process is not streamlined.

We have seen an explosion of data and channels. IOT, ubiquity of devices, bringing with them new sources and types of data much of it increasingly unstructured. 

Traditional processes for capturing data, processing and storing it and transforming it ready for analytics are not 
longer suitable. There is too much latency in the process.

To take advantage of this explosion of data organisations need their analytics and decision processing to move closer to points of interaction and closer to the source of the data, so you can make decisions at the speed of the customer That creates tech challenges:

To do this at scale you need some key ingredients:
Superfast processing for large-scale data manipulation, exploration and advanced analytics Analytics needs to be easily managed, maintained and governed The ability to deploy all this in real time

Lack of technology: The IT infrastructure is often built piecemeal and the business has fragmented of faulty processes and no single approach to customer data collection, management and analysis. They may have solutions in place but these solutions do not communicate with each other and
as a result, collect different or duplicate data across various channels – resulting in an incomplete understanding of customer behaviour

How can SAS help? SAS Customer Intelligence - Delivers optimised marketing campaigns and next best actions Technology provides guided analytical processes to help you stay informed on what actions to take with its 'self-learning marketing algorithm'.