Your Customers are Transforming, Are You?

Part 1

Digital transformation is not a goal, it is a reality. It is not a corporate issue, it is a people issue. Every day, our lives transformed by technology. It is our job at Tahzoo to help our clients connect with their customers, transforming themselves just as their customers are already doing.

Technology has transformed customer experience in fundamental ways. It wasn’t that many years ago that Microsoft’s goal was to have a PC in every house. Today, we have computing devices all over our homes. We speak to our appliances and watch our front door from anywhere on the planet. Computing power is in our hands, on our wrists, in our cars and the very clothes we wear. It has re-shaped the very way we communicate, with each other, with society and especially with the companies and brands we use every day.

Companies no longer just produce goods and services, they are in the business of delivering customer experiences. To be successful, those experiences have to be centered on the customer. Relevancy is in the eye of the beholder. Today’s companies must evoke passion and take customers where they want to be. This can only be done through the innovative use of marketing technology to create outstanding digital customer experiences that differentiate your brand from your competitors.

• 80% of consumers are more likely to do business with a company that offers personalized experiences.
• A brands most valuable customers are 10x more likely to believe personalized experiences are “very appealing.”
• Consumer-facing brands that create personalized experiences are seeing revenue growing 2-3x faster than those that don’t.

Personalization is not just a function of technology. It requires a sophisticated strategy, a commitment to understanding your customers at a very deep level and the ability to deliver differentiated experiences across channels, on any device and within the context of the moment.

It all starts with data. There’s a lot of buzz around “big data,” but there is also a lot of confusion. Companies struggle over what kinds of data exist and what and how that data can be utilized to deliver a personalized customer experience.

Three kinds of data: people data, content data and contextual data.

People data describes the attributes you can know about your audiences; customers, prospects and the market. This includes 1st party data about existing customers, their histories, preferences and behavior as well as traditional customer research like focus groups and surveys.

With the explosion of social networks, blogs and sharing communities, there is a wealth of data that can be obtained to understand what people are thinking and talking about, how they react to different ideas and even the language they use. This 2nd party type of data belongs to the world of virtual ethnography and ontologies which examines how people act, and the language they use, in real life, not how they think a researcher wants them to respond.

Finally, there is 3rd party data. This kind of data, obtained from third party companies like Experian, is often appended to customer records. It includes demographics, psychographics and increasingly interests and proclivities.

Content data, on the other hand, refers to the description of the digital assets that are presented to a customer in such a way as to define the customer experience. Some software vendors talk about digital assets only in terms of images and video. This misses the majority of content which is comprised of text, whether it’s a headline, an article, a caption or the tags and metadata which identify the content to a search engine.

This is important because different types of people communicate in different ways. One person may talk about their lawyer, while another may refer to an attorney. If you are in the UK instead of the US, the similar roles are going to be called solicitors and barristers.

Precise language is very important. People search for content according to the way they use language. They respond to language that is familiar to them and the relevancy of the message itself is dependent on bridging the language gap, both visual and textual.

In addition to people and content data, there is contextual data. This can be as simple as understanding the time and day of an engagement. Or it can become as complicated as including intent in real-time. For example, if I am walking into a store with the intent to buy a specific item, my behavior may be quite different from just browsing around. The former probably conducted online research before coming in the store. The latter may be more open to impulse type purchases at a lower price point, more appealing or simply more visible.