Customer-centric. Data-driven. Two phrases that are commonly associated with the world of retail. This is hardly surprising as the industry is ever-changing and rife with fierce competition. There is also a decrease in customer loyalty to contend with. To regain and retain the consumers’ attention, retailers must listen to what they want and deliver the more personalised, effective and straightforward experiences that consumers are seeking. Considering all of this, it’s clear that for a retailer to thrive and survive, “customer-centric” and “data-driven” must become their bread and butter.
A customer-centric approach puts the customer at the heart of all decisions. This approach is key considering the rise of concepts such as ‘hyper fatigue’ (which sees consumers seeking ways to whittle down the vast amount of content available so that they can zero in on what truly matters to them – check out Mintel’s latest Global Consumer Trends report for more on this). As a retailer, to be customer-centric is to understand the value of each customer to your business. This concept can be summarised as customer lifetime value (CLV) – a metric that helps you identify your most valuable customers and comprehend how much they are worth over the course of their relationship with your business.
Why is it so important for retailers to have this lifetime view of their customers? Well, it essentially boils down to the ability to make informed decisions. Also, it’ll help you stand out to customers and reduce the likelihood of being cast aside in their ‘hyper fatigue’. In order to create this lifetime view and reach your goals, you need the right sort of information and it needs to be centralised, organised and analysed effectively. By tracking CLV, you get information that can lead you to allocate your budget and resources efficiently to maximise the return on investment.
Tracking CLV can also help you to optimise your pricing. For example, you might be willing to offer discounts to high-value customers, knowing that they are likely to make more purchases over the course of their relationship with your business. Capitalising on these opportunities can help retailers move closer to their financial goals. Overall, whether the name of the game is acquisition, retention or nurture, you’re likely to see more value for money when you measure CLV.
So, getting to grips with CLV can mean better informed decisions? Fab. More efficient use of resources? Great. Optimised pricing? Kerching! But how specifically can Google Cloud help a retailer to become more customer-centric and data-driven? Enter BigQuery.
Google’s BigQuery is a fully managed data warehouse that allows you to analyse large and complex datasets quickly and easily. It provides the tools that you need to collate all of your various data and build a single customer view. BigQuery alone won’t do everything for you but combining your wealth of data into a single source of truth allows for comprehensive analysis of customer behaviour and purchase data. When you understand these better, you’re more likely to also understand your CLV better. As we’ve already alluded to above, the more you understand your CLV, the more you can use your data to make those informed decisions that effectively meet your customers’ needs and wants.
You can also take your understanding of your data to the next level with BigQuery’s machine learning extension, BigQuery ML. Building, testing, iterating, deploying and continually adjusting analytical models can consume a significant amount of employees’ time. BigQuery ML can lessen this by doing the heavy lifting in the analytical model life cycle, allowing a retailer’s workforce to step back and gain even more actionable insights from their data. For instance, a retailer can use its machine learning capabilities to take a proactive approach to pricing (see Sigma Sports). You can also use these capabilities to personalise the customer experience, making recommendations based on past purchase history and other data points (check out our work on the GCN app).
Thanks to technologies such as BigQuery, you can see that Google Cloud can help retailers explore their wealth of data and get better acquainted with their customers, i.e. it can help retailers be more customer-centric and data-driven. Armed with such tools, retailers can get to grips with their CLV; in turn, this increases the likelihood of taking actions that will motivate your customers to stay engaged and loyal to the brand.
So, why should retailers be tracking CLV? Well, it’s so you understand how exactly your customers contribute to your business and also how to appropriately manage your resources. It’s also because it enables you to make decisions that better meet your customers' needs, stand out to them in this competitive landscape, and keep them happy. The happier your customers are, the less you’ll have to worry about decreasing customer loyalty.
If you need help with tracking CLV, Google Cloud and its technologies are always here to support you with deriving valuable insights from large and complex datasets. In short, take advantage of Google Cloud and use your data to place the customer at the heart of things, i.e. be truly customer-centric and data-driven.
If you’re a retailer who’s ready to become more customer-centric and data-driven, check out Ancoris CMOLab to see how we can help you from today. Get to know your customers better and optimise your marketing spend all within one nifty solution – get all the info you need here.