Digital Transformation in an Ever-Changing World

Digital Transformation in an Ever-Changing World

Digital transformation is not an end-goal to be attained; it’s a new daily reality for all businesses. It’s not a corporate issue; it’s a people issue. Every day, our lives are being transformed by technology in ways we couldn’t even imagine a decade ago. Here at Tahzoo, we help companies better connect with customers, providing the leadership needed to transform their approach to technology during these unprecedented times.

As recently as last year, we spoke about how technology was transforming customer experience in fundamental ways. My, how times have changed. Today, we see that it’s not just technology that is transforming. It is the intersection between technology, society, politics and so much more that is profoundly changing the ways people experience and engage with brands.

It wasn’t too many years ago that Microsoft announced its audacious goal to have a PC on every desk. Today, we speak to our appliances and monitor our front doors from anywhere on the planet. We also engage with people via digital experiences, almost to the exclusion of face-to-face conversation. We buy everything online, our children go to school online, we debate our worldviews online, and we interact with our healthcare providers in ways we would have never thought possible in 2019. The world around us has re-shaped the very way we communicate, and it is here to stay.

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

Every company seeks to produce quality goods and services. But beyond building great products, companies are also in the business of delivering quality customer experiences. We live in a world where most companies are re-thinking their fundamental business models to survive.

For example, restaurants have refocused their experiences around take-out. They are inventing ways to keep French fries crisp and hot for 30 minutes. Last year, we suggested that the experience of the meal has become more important than the food itself. Now, our new experience includes eating that meal out of paper and plastic containers in our living rooms.

Many industries are learning how to replicate a customer’s experience with their products into the home. Online shopping has accelerated. Video conference doctor visits have re-invigorated the age-old house call. The office is no longer a place to gather; rather, it has become more of a state-of-mind.

To be successful, companies must redouble their efforts to provide experiences centered around the customer. Relevancy is in the eye of the beholder. Today’s companies must evoke passion and take customers where they want to go, no matter how virtual the experience is. The accelerated use of marketing technology to create an outstanding digital customer experience and differentiate a brand is what makes all of this possible.

The world has moved past the abstract idea of “personalization.” Now “contextualization” has become the watchword. It is the delivery of an experience that is contextualized, not just by what you know about your customers, but by what you understand about the world in which they live. Contextualization incorporates time, location, outside influences, and even states-of-mind. Your customers are living in the real world, in real-time and they expect their experiences to reflect that reality.

Contextualization requires more than a technology investment. It requires a sophisticated strategy, a commitment to understanding your customers at the deepest levels. It requires that companies deliver differentiated experiences across channels, on any device and within the context of the moment.

Our new approach to Contextualization starts with data. There continues to be a lot of buzz around “big data,” but we also know there is also a lot of confusion. Companies struggle over what kinds of data exist and what or how that data can be utilized to deliver a personalized customer experience.

Let’s take a few minutes to unpack Tahzoo’s approach to Data-driven Contextualization.

Three Types of Data: People, Content, and Context People Data

These are the attributes you can know about your customers, prospects, and the market in general. This includes 1st party data about existing customers, their browsing history, preferences, behavior, and traditional customer research like focus groups and surveys.

We’re living virtual lives that challenge our relationships via social networks, Zoom encounters, and newly defined digital communities. There is a wealth of 1st party individual data that can be obtained with permission to better understand what people are talking about and how they react to different ideas.

The compilation, curation and analysis of 2nd party data is called “Virtual Ethnography.” Virtual Ethnography (and its first cousin - ontologies) examines how people act in the abstract and the language they use. It looks at customers from a real-life perspective, not simply how they respond to a focus group.

Finally, there is 3rd party data. This is obtained from companies such as Experian, where data is often appended to customer records. It can include customer demographics, psychographics, interests, and proclivities. Marketing and advertising executives have traditionally used 3rd party data to target ads and content, but this data is also becoming central in providing superior digital experiences.

Content Data

Digital assets (including content) are organized and presented to a customer in a way that defines their customer experience. Some software vendors talk about digital assets only in terms of images and video, but we include textual content in the definition of a digital asset: headlines, articles, captions, or the tags and metadata which identify content to a search engine, are all assets.

People communicate is wildly divergent ways. One person may talk about their lawyer, while another may refer to their attorney. If you are in the UK, you might refer to your solicitor or barrister. The nuances of semantic choice can’t be underestimated as companies seek to improve contextual experiences. People search for content the way they use language. They respond to language that is familiar to them and the relevancy of any contextual experience is dependent on bridging that semantic gap.

Contextual data

A customer experience can be improved by simply understanding the time and day of a digital interaction. For example, if you visit with the intent to buy a specific item, your behavior may be very different than if you were leisurely shopping for on-line items to buy. If you go directly to a brand’s ecommerce website first, it’s likely that you may have already conducted some type of online research before logging into the store. These nuances make all the difference in how companies influence the customer experience and reduce their “path-to-purchase.”

Semantic Strategy

Semantic Strategy is understanding what content is being accessed by people and then using that insight to define the right language by which to communicate. By understanding the structure of the language being used, we can build ontologies and content models that help identify the essential meaning. From there, we can generate taxonomies to inform experience design and search.

Once you know your audience and have the right content, you will need to decide who gets what content, when, where, how and why. This requires a new level of sophistication. A new “Intelligence” is needed to impact the customer’s contextual experience. It the province of using artificial intelligence, machine learning, and deep learning.

Artificial Intelligence, Machine Learning and Deep Learning

Artificial Intelligence

Artificial Intelligence is the means by which technology is used to examine various user interactions and make decisions faster than human beings can. For example, companies are beginning to embrace facial recognition or pattern recognition, the digital equivalent of finding a needle in a haystack. This can make all the difference when building a contextual experience for a user.

Machine Learning

Technology is available to take those haystack needles, or the patterns found therein, and use the right algorithms to predict when and where a user is most likely to find the next needle. In machine learning, data scientists use inductive logic, clustering and Bayesian networks to achieve these goals.

For example, machine learning may discover that people who like cute cats are nice. But how can you recognize a cat? Is it furry? Does it have a tail and run on four legs? The characteristics described above are also the same for a rat. So, the challenge is, among other things, to define the quality of “cuteness.” Machine Learning can do that.

Deep Learning

This is the technology needed to recognize any abstractions in the content. Deep Learning uses the algorithms produced by machine learning to better understand user behavior. Deep learning looks at all of the variables and determines a “probability vector,” or educated guess. From that guess, deep learning assigns a confidence level to its predictions. In our previous example, a cat has a much higher probability vector of being cute than a rat. In a retail scenario, deep learning can be used to help determine the probability that a customer would choose a touch screen PC over a basic PC.

This is the technology needed to recognize any abstractions in the content. Deep Learning uses the algorithms produced by machine learning to better understand user behavior. Deep learning looks at all of the variables and determines a “probability vector,” or educated guess. From that guess, deep learning assigns a confidence level to its predictions. In our previous example, a cat has a much higher probability vector of being cute than a rat. In a retail scenario, deep learning can be used to help determine the probability that a customer would choose a touch screen PC over a basic PC.

Multi-channel Dynamic Publishing and Presentation

Once you have implemented your “big data” strategy and run it through deep machine learning, an integrated technology strategy can help you get the right content to the right person at the right time. A supporting MarTech stack makes it possible to present your content based on individualized data profiles.

A generation ago, advertisers spoke to customers through billboards or three broadcast TV channels. They advertised four major magazines, where media buyers knew they could capture the greatest number of viewers. Ah, the golden age of mass advertising. Unfortunately, those days are gone forever.

New communication channels are being launched every day. In our communications world, e-books and Twitter are still regarded as teenagers. Pinterest and Instagram were only launched in this decade. And we are still not sure about Siri or Alexa. But one thing is certain: consumers are engaging with brands in myriad ways with myriad devices. In the U.S., the average person connects with eight different social apps a week. Smartphone penetration in Europe is 65%, in North America 64% and over 53% in China. There is an estimated 3.7 billion email accounts worldwide and 269 billion emails sent every day. Our daily life is filled with multi-channel communication.

Brand messaging cannot be limited to what we have always known. Modern consumers demand personalization in every channel and on any device, regardless of platform. This is the challenge we face in digital publishing. We must embrace a sophisticated, multi-dimensional solution that incorporates content management, digital asset management and dynamic publishing.

To be successful, today’s marketers must embrace multi-channel dynamic publishing. Their presentation layer must be integrated to form a single content hub. Only then can these systems work together to provide the means to meet customers in the context of the moment.

Your customers expect your brand to recognize them, to know what interests them, and to provide them with a personalized experience. Brand loyalty is the reward for a well-delivered digital experience. Today’s brands must engage with customers in an increasingly complicated digital world, understanding that it is becoming easier and easier for those customers to switch brands. This makes customer loyalty an even bigger chalice to attain.

Tahzoo understands the emerging digital dynamic between people and brands. We understand what it takes to deliver a contextually relevant customer experience. By using the right combination of data, strategy, design, and technology, Tahzoo can help brands connect to customers by making their digital experiences a contextual reality. Or, as we simply like to say, we help customers “Build Better Moments.” We deliver contextual experiences for global customers like Starbucks, Transamerica, Colgate, Deloitte, Boston Consulting Group, Jaguar Land Rover and Sodexo.

Let’s talk about your transformation.

For more information, visit or contact us at [email protected]

John Kottcamp

Chief Marketing Technologist

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