In this opinion piece, Camila Lima (pictured below), head of production marketing at Invigor Group discusses the importance of CMOs using data-driven, customer-centric strategies to keep local brands competitive against the rise of digital giants such as Amazon.
As the definition of customer centricity is evolving over time, it is imperative that Australian brands consider how they can navigate the next wave of digital with customer-centric solutions.
With the technology readily available, customer expectations upon brands have increased and the pressure to outperform competitors getting more intense. The connected consumer has expectations like never before, and this presents a unique challenge to brands to be immediately responsive and omnipresent to their customers’ needs across multiple platforms.
Customers now have an expectation they will not be addressed in mass communication, but rather with an assumption that their individual needs, buying habits and inclinations are going to be addressed. Equally, so has the approach to meeting them through utilising data which helps shape the marketing campaigns for beloved Australian brands. When we watch Beerenberg launch new look labels, or Allen’s bring back Green Frogs, there is a case to be made that every pivot is based on data assessed about their customers. For many retailers, this honed-in approach may seemingly be reserved for brands with huge marketing budget, but the reality is far more accessible.
It is time to re-educate Australian retailers that the opportunity to adopt the technologies and practices that players like Amazon use are available. Particularly with bricks and mortar retailers, the focus on aggregating data-driven strategies will be not only the way to sustain operations, but to compete effectively.
Brands need to be ready to embrace solutions that allow more insightful decision-making, and integrate the frameworks that make this possible. Tools that are based on accurate, real-time data which provides actionable insights derived from multiple data types and sources. It is also time that brands utilise machine learning algorithms for real-time insights and predictions over time to allow for improved operations, increase of profitability and scalability.
These are not just mission statements for a strategic direction report, but brands need to understand what the difference is between digital transformation, data consolidation and analysis. Big data has been around for years now and many retailers still haven’t solved that puzzle. We know that having huge amounts of data sets can be valuable, combining data sets even more so, then applying prediction, machine learning, and of course, human analysis and opinion to the data now gives it a three-dimensional feel and practical application.
We need to ask how Amazon is doing it, and why can’t every Australian retailer do it?
Retailers should be seeking to partner with those who can help them fully understand their customers. For CMOs entering this space, such a commitment to data can be daunting, but like any relationship, once finding a suitable data partner (which there may be many fine suitors), it’s a two-way street. The technology is now at the level where it is functionally robust enough to work across industry and now cheap enough that anyone can use it. The issue this can create is where to start, with who and how?
What expectations should CMOs have on themselves? What plans are they putting in place to utilise the mass of data they have available to them? And how can they deploy predictive marketing and stay ahead of the competition? It should be more than managing a social media strategy or working out your cost per acquisition. It must be about having a full grasp of who your customers are, and what each journey with them could look like.
Ultimately, customer centricity is about storytelling, which can only be done effectively when based on the data that is collected about the customer. Fully comprehending where the customer is in their journey and the emotions that surround a purchase is vital to achieving the tailored one-on-one interactions that customers are seeking. Understanding and creating language to put around the data helps to create a picture of who the customer is and what their underlying wants, needs and desires are.