Are marketers ready to ride the next wave of digital transformation?

Written by
Harjot Dhawan

The state of digital marketing in 2020

We have come a long way from the first banner ad on a website 25 years ago which marked the start of digital marketing. Then we moved on to social media, SEO, in-app marketing, emailers, etc. The dynamics of our day-to-day life are changing rapidly because of our evolving interaction with technology. A few years back we couldn’t fathom the thought of talking ‘to’ our phone in addition to using it to talk to other people. It’s probably still weird to think that refrigerators (smart ones) now have the ability to ‘tell’ us that we are running out of ice cream. And what our digital ecosystem will look like in 10 years is a mystery but the developments we see today might give us some idea about what the future holds.

What’s next?

Taking a sneak peek at how prominent technologies of today will create a more efficient landscape for digital marketing and advertising:

Big Data – the foundation: The more data you can gather about customers and their preferences, the more accurately you can predict future demand, sales, and marketing budgets. It plays a critical role in reducing variables and hence customizing marketing tactics for individual customers, leading to a better brand experience. With big data at the core, the access to and analytics of this data (job for AI) will be the game changer in enabling brands to have meaningful conversations with potential customers.

Example: Amazon leverages user’s behavioral data to personalize the product ads shown to the users. Remember the “item” you checked on amazon that is following you everywhere – Facebook, YouTube, Instagram, etc.

Blockchain – making online ads great again: Considered to be the next big thing in the world of digital advertising, primarily because its aim is to reduce ad fraud by building transparent ecosystems and a secure flow of information directly between advertisers and end consumers. This translates to more data privacy for consumers, and higher RoI on every advertising dollar spent by brands. At the moment blockchain tech specialist firms are collaborating with marketing firms to help them enhance their programmatic capabilities, but since the blockchain technology will take 5 to 10 years to mature, it’s impact on marketing will also be realized as the technology becomes more advanced.

Example: IBM (Blockchain solution provider) worked with the likes of Unilever, Pfizer, Nestle, McDonald’s in a year-long pilot which completed last year, to create a zero leak efficient ad buying system. Unilever saidthat they saved 2 to 3 percentage points in this exercise, and now the goal is to go further.

Internet of things (IoT) – connecting people and things: With higher internet speeds and ubiquitous connectivity, a lot of appliances and machines are turning digital. They have the ability to record data, respond to commands, and interact with our phones. The ‘smart home’ concept is building on this phenomenon. As more devices become connected, it will lead to more platforms for marketers to engage customers and get more data about their preferences.

Example: Burger King executed a campaign leveraging IoT to great success — they launched a “Whopper for a Penny” campaign. Any customer within 600 feet of their competitor McDonald’s would receive an alert on their smartphones and be directed to the nearest Burger King outlet.

Artificial intelligence (AI) – driving efficiency in real-time marketing: Yes, there is a lot of hype and speculation around AI but fact of the matter is that we are atleast decades away from human-like robots roaming around us. So while super intelligence and general intelligence AI (which are beyond or at par with human capabilities respectively) are not foreseen in the near future, it will be interesting to see the impact of narrow AI in the digital marketing mix because it will give us critical information for faster and more accurate decision making.

Example: IBM Watson Advertising: Its product WEATHERfx interprets and normalizes weather elements, sales, and/or consumer data and defines the condition mixes when weather is most likely to drive behaviour, putting the most relevant brands in front of the right people at the right moment.

Machine learning (ML) is the subset of AI that makes it really interesting by improving the performance of AI over time using data. Examples include show you content recommendations based on your past views, creating lookalike audiences, running programmatic ads, etc.

Natural language processing (NLP) enables AI to hear and speak, and is adding another dimension to the marketing mix with chatbots, semantic analysis, voice search capability etc., which means that brand<->consumer interactions will become more real time, which is good for the impatient consumer. A use-case of sentiment analysis within NLP which is being worked on is interpreting conversations to analyze the customer’s sentiment towards the brand. If you are talking to a friend about the new Alexa or Google Home device you just bought, and the device interprets that conversation to infer that you are enjoying your experience with the product just by listening or reading your comments online, then that is NLP and AI at work, and this allows marketers to see customer data in a new light.

To sum it up, we are just scratching the surface of digital marketing today because the underlying technologies are for the most part, still in their early stages. I have looked at their broad-level implications in digital marketing, but they have promising use-cases in healthcare, banking and finance, insurance, energy, automotive industry, and so on. This clearly shows that they will be impacting multiple facets of a customer’s life, beyond how they consume information, making it imperative for brands and marketers to understand and embrace them.

Written by
Harjot Dhawan