As consumers, we live in a digital ecosystem almost without realizing it. We interact with brand touchpoints many times a day, and our brand perception is shifting and evolving in each of these. More than this, we buy into their brand rather than buying products from companies. Customers for any product or service now expect the personalized touch and a tailor-made customer experience delivered to their screens.
The explosion of big data has allowed businesses to rethink and reshape their brand attitude and tone. However, it has also posed a more pragmatic challenge of maximizing the potential hidden in the huge data sets they have built over the years. This is where customer analytics comes into play. Analytics can turn the massive amounts of data you already have on your customers into insights. Remember that this is something different from traditional analytics or business intelligence.
Whereas traditional analytics look to the past to predict trends, customer analytics look for what a customer will do as an individual.
The ability to leverage and maximize the value of this treasure trove is now more mission-critical than ever. Building relationships with customers now involves more frequent but far shorter interactions. Yet the brands rely on this to build the lifeblood of any company – brand loyalty. Customers have more access points to their service provider than ever before. For instance, they can interact on the company’s website or app, phone, or social media accounts. These interactions take less time than an in-person visit, but they happen much more frequently. They are also not as profound as face-to-face interactions, making it even more important to have each one count.
Companies need to take advantage of all of these touch points and interaction moments to provide real value. The only way to do this is to be relevant in ALL areas of messaging, timing, and to ensure these are relevant to the customers’ context.
But how does one become relevant? The first step is understanding who your customers are.
Let’s put it in Context
Contextual relevance is the most important factor in extracting value from data. Understanding human behavior but not being able to apply it to common-day contexts, such as where someone is or what their previous actions were in the last hour, will only allow a company to understand better what has happened in the past. There is little value in living in the past when a business’s value is counting on what happens in the now. This is especially true when considering a customer’s experience. If the content ignores a customer’s context, the brand’s marketing efforts will be futile, the needs of their customers will go unmet, and customer relationships will diminish significantly.
Real-time reactions
So, how does a company use data to deliver relevance? The answer boils down to having actionable insights available at your fingertips. To leverage the knowledge of the customer context, companies must move to a process that combines long-term historical insights with up-to-the-minute processing of real-time behavioral data. Companies must then use the enormous amount of existing user data to constantly create connected user experiences, compared to those produced by technology companies dependent on web traffic activity and information alone. Productively utilizing customer data allows a company to determine what customers are most interested in and create a personalized experience where content, products, and services are presented to customers before they realize their needs. As customers’ expectations of their favorite brands increase, they have more affinity for those that offer more pertinent information and instruction and add convenience to their lives.
Marketers must be able to truly manage the conversation with the customer, both in and outbound. Companies can do this by using their data to deliver the most relevant, timely, and contextually-aware actions that match the needs of each and every individual customer. When a company or brand can execute on the insights gleaned, they’ll become transformative in how they approach marketing.
Taking the customer journey full circle
By leveraging the context found in data, brands can provide customers with an optimized experience that is more relevant and consistent across all channels. Personalized service can be adapted to their present needs and interests and tied to the complete customer context – their location, most recent purchases, complaints, etc.
For a company, the value of processing customer data with analytics software can be about optimum marketing results, with more precise targeting, more connected experiences, and increased campaign efficiency. This allows companies to acquire the right customers, provide them with excellent service and products, and be more focused on which customers to retain at what cost. The value of customer data is beneficial for both the customer and the service provider as they genuinely begin to operationalize insights on customer data and behavior.
But crucially, data itself isn’t smart – it takes a level of processing to develop the insights that drive businesses forward. Companies can only utilize data to its full potential by harnessing and harmonizing the assets at their disposal, unifying multiple entry formats, systems, and processes. Only once this has been achieved can the power of AI-powered programs and platforms drive actionable insights to boost customer engagement. Creating end-to-end systems like these mimics the customer journey, turning dumb data into true connections between business and customer.
