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Potential for businesses

Watch Dr Timo Dietrich discuss using digital touchpoint data to deliver personalised products and consumer data to improve car maintenance operations.
Have you ever wondered how much time people spend online to research before buying a new car? Well, Google has done a study and looked at the amount of touch points that a potential buyer has from the first time they Google the car that they wanted to buy to actually test driving that car. And the study found that there is an average of 24 touch points, of which 19 are in fact digital. This is truly remarkable, because before our digital era, all you had to do was run a TV, radio, and maybe newspaper ad, and then wait for people to come to your dealership and potentially buy the car.
Now, you need to think of an additional 19 touch points, and how you can be of value to your potential buyer at every one of those touch points. That’s a really big ask. With each of these touch points, we as marketers can learn about that potential customer. We learn what they like, what they’re interested in, and what they want to hear from us moving forward. Customers, as a result of all this, have obviously become more curious, demanding and impatient than ever before.
We as marketers need to use the massive amount of data that’s available to us so that we can be of better assistance to the customers and potential customers when we move them from our awareness to our consideration and purchase stages. We call this the age of assistance– the era where brands will need to deliver more value to inquisitive customers. And in fact, customers expect us to deliver this relevant and personalised communication, whether that is offline or online. And the better we understand our customers, and the more data we have, the more contextually relevant we can be. So up to this point, I’ve been talking about the buyer journey. But great customer service doesn’t stop at that final sale.
In fact, this is only the true starting point of a lifetime relationship between the brand and the customer. See, every organisation aims to build relationships with their customers for lifetime, whether that’s Netflix, Coca-Cola, or any car brand. They all want you to be a customer for life. Take Tesla, for example. They build electric cars that can almost drive themselves using sensors and software. The sensors are on the inside and outside and collect data 24/7. The data is used to generate highly data dense maps, showing everything from driving behaviour to location of hazards. But all cars can also receive a centralised update to repair these vehicles through a software patch.
Tesla can look after the cars without the customer even needing to worry about bringing the car into the shop. Of course, that does not yet work for all repairs, and sometimes the car still needs to tell you to bring itself to the shop, but the point is the more seamless this becomes, the more likely it is that you will be happy and a loyal Tesla customer for a lifetime. So in summary, marketing technology now allows us to track customer journeys like we have never been able to before. As everything gets recorded and people spend more time online, we can process this data, analyse this data with machine learning capabilities, and help us interact with customers more efficiently and appropriately.
Remember, as a good marketer we always give value first, and then we sell.

The first major application area for big data analytics was selling products and services to consumers. Businesses have been collecting huge amounts of customer data to analyse how they can deliver better products and services to their customers.

Data from digital interactions

From the early 2000s, consumers turned more often to the web for shopping. This presented opportunities for businesses to learn more about their customers than ever before. Customers have been:

  • searching for products online
  • comparing different models on websites
  • signing up with their address details before making purchases.

All these details are recorded. With each digital interaction, or digital touchpoint, comes the opportunity to gather more customer data. As you can imagine, over time, businesses have amassed large amounts of personal information and preferences.

Personalisation and improvements

There are two general ways businesses use this data.

Individual level

They consider in-depth the data of each customer. This enables them to deliver personalised products, services, and advertising. Interactions are targeted to the preferences and habits of the customer.

Collective level

Businesses also consider data from many customers to find commonalities. They determine similarities among customers to help improve the business operations or motivate a new product or service.

The cost is privacy

So, where does this leave us as consumers? Obviously, we benefit from personalisation and new products and services. However, there’s no such thing as a free lunch. We are paying for these improvements with our privacy.

Businesses often provide free services in exchange for our personal information. We register on their site with our home address and credit card details. We share our list of friends. We disclose our preferences for food, travel, and sport. We even train their algorithms by tagging our family members in photos, and letting them know whether a page answered our questions.

A data-driven economy

All this has given rise to a new economy, driven by our data as the commodity. Indeed, the majority of the most valuable public companies nowadays are all data-driven technology companies: Apple, Microsoft, Amazon, Alphabet, Facebook, Alibaba, and Tencent.1 When so much of our data is being used and traded, we as consumers should have some influence in the market. In the next step we will explain how the government is helping to achieve this.

Your task

Watch the video by Dr Timo Dietrich, to learn how data collected from digital touchpoints can help car manufacturers deliver more personalised products, and how Tesla uses data collected from its consumers to improve its car maintenance operations.

Have you heard of any other examples where big data is improving business operations?

Share your thoughts in the comments.


Video references

Accompanying text references

  1. Statista. The 100 largest companies in the world by market value in 2019 (in billion U.S. dollars) [online]. 2020 [cited 2020 Apr 29]. Available from: 

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Big Data Analytics: Opportunities, Challenges and the Future

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