In recent years, 'Big Data' has gained almost a cult status. According to Google Trends, interest in big data began rising exponentially around 2011 and is forecasted to keep growing.
While some think big data is an in-vogue term created and propagated to generate excitement without any measurable ROI; they couldn’t be further from the truth. Big data revolution is real and has the potential to dramatically change businesses and enhance experience of retailers and brands that are willing to take advantage of it.
Big data evolution
In the 80s, data collection, storage and processing were very expensive undertakings. Handling one gigabyte of data could run into a million dollars. Today, we collect, process and distribute terabytes of data at a small fraction of the cost. In addition, over 9 billion Internet-enabled data collection devices exist these days and are projected to reach 50 billion by 2020!
Personal connectedness through social networks has also led to data being generated in huge volumes, high velocity and variety of formats such as videos, pictures and music. This is big data!
What is the value of this data and how can retail brands take advantage of this surge?
The answer lies in understanding the modern customer. The modern consumer is always online, selective about what advertisements to view, when and with whom to share information and can ‘switch off’ by simply unsubscribing. They are 'grazers' without a clear purchase path. They could begin browsing on their smartphones, continue on their laptops and go to the brick store for the final purchase. They demand that the retailer know them very well and provide seamless shopping experiences across all touch points, instantly 'remembering' what they have done on each device.
Today’s consumer is savvy and aware that retailers are collecting their data and expect to see returns in terms of value, rewards and pleasant shopping experiences.
Rewarding customers through customer science
About 75 per cent of data collected today is not being used to uncover information, the so-called 'dark data'. The challenge is that most businesses do not know how. Customer science is the missing link between big data and improved customer experience. Customer science unlocks information about the customers' behaviours, influences and motivations (BIMs) and subsequently builds tools and solutions to provide personalised experiences and value. These solutions in the form of intelligent product recommendations, offers, pricing, personalised ideas etc are designed to make the customers’ life easier. In return, retailers earn long-term loyalty and gain competitive advantage.
Applying customer science to big data may seem like a difficult journey. Here are some principles to help you navigate your big data quest.
How best to navigate your big data
1. Start now
Most retailers are already collecting a considerable amount of data. Although this data may not be in a format that can be easily analysed, retailers must immediately commit and invest in collating and extracting as much information as possible. Additional external data adds interesting dimensions to existing data and drives good value. However, other data sources should be sought only after a thorough understanding of current data with clear goals of what you want to accomplish with new data.
2. Treat customers as individuals
Analyse data to understand each customer’s BIMs, then apply customer science to personalise solutions to earn customer loyalty. Businesses that have access to individual customer data no longer need to rely on large demographic segments which have been used for marketing previously. Retailers must strive to understand every customer and tailor laser-targeted offers.
3. Use big data everywhere
Almost all aspects of retail business can benefit from big data analytics. From strategy formulation to pricing optimisation, big data analytics is not just about marketing. For instance, applying big data analytics and customer science to inventory management can greatly reduce loss caused by inventory distortion.
4. Be selective
Big data analytics is exciting but not all insights derived are actionable. Retailers must act only on non-trivial and robust information. This means rejecting some data and conclusions with the assistance of data science experts with strong domain knowledge.
5. Be innovative and experimental
The big data environment can greatly facilitate testing and innovation. You can move from traditional A/B testing of a few factors to scientific design of experiments where you can investigate hundreds, perhaps thousands of factors in a single experiment. Retailers should take advantage and ensure that ideas are scientifically tested prior to rollout.
6. Reward customers
Customers are aware that their data is being collected and have entrusted us with it. Retailers should reciprocate by using it responsibly and making decisions that benefit customers and make their lives easier.
This is an exciting era in modern retail, traditional selling is amalgamating with science to create a new ecosystem of scientific decision-making. From tactical solutions such as dynamic personalised pricing to strategic visions such as earning the customer's long-term loyalty, big data plus customer science are making their way into the forefront of the retail business. The key to longevity and success is making sure that we remain responsible custodians of customer data and ensure that all decisions are customer centric. If the customer wins, we all win!
The article is written by Dr. Anthony Kilili, Capability Director – Communication and Media, dunnhumby India