We live in an era of digital Darwinism, one where technology’s impact on society evolves with every iteration, innovation and disruption. As a result, consumers are empowered with new capabilities that influence behaviors, expectations, and cultural norms and values.
Retailers, as well as most organizations across every industry, are struggling to keep up with the changes and the ability to react and innovate. Companies that don’t keep up with outside trends and inside capabilities find themselves on the wrong side of digital Darwinism.
Altimeter, a Prophet company recently partnered with SAS to develop, “The Real-Time and Predictive Commerce Playbook for CMOs,” a research-based guide for CMOs to navigate digital Darwinism and help their businesses grow.
The Same Disruptive Technologies That Powered Customer Evolution Can Also Fuel Digital Transformation
Retailers must not only respond to disruption, they must build new models to adapt, test and learn and deliver new value in real-time. The irony and opportunity here is that with disruptive technology comes the ability to become more human, customer-centric, service-oriented and hyper-personalized to engage customers and deliver experiences in real time. The real innovators and disruptors in retail concentrate data, digital transformation and business growth on…people.
Enter real-time analytics.
Harvard Business Review Analytic Services – along with Accenture Applied Intelligence, Intel and SAS – studied the importance of real-time analytics in defining CX. The results highlighted the impact and benefits of brands that connect CX through business strategy driven by real-time data and analytics insights. Some of the important findings on the importance of real-time analytics in digital transformation include the following:
- 75% say they’ve increased their spending on real-time customer analytics solutions over the past year.
- 50% said their use of real-time customer analytics has provided them with a significantly better understanding of the customer journey.
- 58% said their companies have already seen a significant increase in customer retention and loyalty.
- 50% said their use of customer analytics has generated significant revenue growth.
Real-time adds value.
Digital Darwinism continues to evolve. Customers, too, are evolving. Real-time customer analytics give modern brands an edge to not only keep up with and improve customer experiences, but also drive bottom-line business value. The study also uncovered several attractive and lucrative benefits to companies where CMOs built out advanced real-time data and CX capabilities:
- 85% report improved customer experiences.
- 58% claim speedier decision making.
- 54% streamlined operations/increased sales and marketing efficiencies.
- 40% increased innovation.
- 33% better ability to compete with digital disruptors.
So, what’s next?
Research already shows that competing at the speed of the customer delivers business-level impact and outcomes. Yet despite the benefits offered by real-time customer analytics to enhance customer experiences and drive business growth, the vast majority of retailers lack these capabilities today. As they stall, competitors rewrite the standards for CX, and customers reward those brands, not only with their business, but also their loyalty and advocacy.
The deeper retailers’ understanding of shopper behavior and lifestyle preferences, the better response and personalization can be. As retailers build the skills and capacity required to operate in a real-time world and engage at the speed of the customer, what happens when you can also start to predict how tastes and trends will evolve?
Enter predictive commerce.
Now, technology has advanced to the point where artificial intelligence (AI) and machine learning are here and readily available to everyday businesses. Technology, and more specifically predictive analytics, are only getting smarter. Systems can now learn from data to help businesses respond even faster and with greater precision. More so, with the right systems and programming, machine learning can even outpace the speed of the customer and empower businesses to predict shopper behaviors, anticipate needs and stay ahead of shopping trends.
In marketing, for example, predictive analytics can be used to optimize campaigns by determining likely customer responses or purchases, as well as promoting cross-sell opportunities. Predictive models can also help businesses attract, retain and grow their most profitable customers. On the back end, AI and machine learning have been used to forecast demand, as well as set pricing while also being the best way to predict stock and staffing shifts.
Setting the Stage for the Next Generation
This sets the stage for a next-generation opportunity for forward-thinking retailers to grow and prosper— predictive commerce.
Real-time analytics allows businesses to more effectively compete in the now. Predictive analytics gives businesses the aptitude to compete for tomorrow—today.
This is the foundation for predictive commerce: the ability to anticipate customer needs, expectations and preferences at the precise moment of need or before customers recognize they have that need. Additionally, with predictive commerce, retailers also have the ability to dynamically recommend products, anticipate personalization needs/timing, and even predict shopping trends months from now.
The most successful retailers are, at their own speed, building an integrated model around customer-centricity; one where data, expertise/capabilities, collaboration and experimentation are governed and sanctioned at the top, i.e., investors, C-suite, board and shareholders.
The speed of the customer is only accelerating. Organizations that make real-time analytics and predictive analytics the center of business, the core of innovation and the pinnacle of customer-centricity will continue to deliver meaningful and value-added customer experiences while also future-proofing the business.
Download the report, “The Real-Time and Predictive Commerce Playbook for CMOs,” today.