Marketing is no longer dependent on assumptions and gut feelings. Today, data-driven innovations are the goal of marketers. Data has the potential to be your most valuable marketing resource. With the right information, you can create scalable and repeatable marketing processes. This is the real value of DDI because you can run your campaigns based on data-driven innovations so you can focus on the creative side and optimize effectively.
What is data innovation?
Data-driven marketing is essentially the strategy of using customer information for optimal and targeted messaging. Due to the increasing quality and quantity of marketing data, many companies have started to implement this approach for creative production and automation. Data driven decision making is the process of answering questions like who, when, where, what message is taken and made part of your future marketing strategy.
What will shape data-driven innovation in 2020?
In the United States, however CCPA, valid from January 1, 2020will have a significant impact on corporate data protection initiatives in all sectors. It is considered one of the most stringent data protection laws in the United States and offers California residents the ability to control how companies process their personal information. Businesses must now respond to requests from residents to access, delete, and disable their disclosure or sale. In addition, companies need to consider a number of CCPA-specific requirements when updating their data protection programs, such as: B. Opt-out measures and the need to stop selling consumer data on request. With this in mind, in addition to the rise of artificial intelligence and machine learning, data-driven strategies will be shaped by these factors if companies want to stay ahead of the curve.
How data-driven innovations will change in 2020
In addition to factors such as GDPR and CCPA, there will be a few more examples of data-driven innovation trends in the coming year. Data-driven insights are constantly evolving and can offer companies added value in ways that were previously not possible.
- As artificial intelligence and machine learning continue to improve, companies can use faster, more accurate methods of processing data on a large scale. Optimizing ongoing campaigns will be much easier as AI and machine learning skills evolve.
- Retargeting ads are being used more and more. As consumers constantly switch between different platforms and devices, retargeting is becoming increasingly important. In this case, a brand may use data-driven advertising to target someone who has switched to other pages and to remind them of what they have viewed on their website. These can be particularly useful when a customer leaves their shopping cart because the ad can remind them of what they have left and push them to a checkout counter.
- Personalized marketing based on data is becoming more general. Using a data-first approach, marketers can create email marketing plans that offer individual customers a high level of personalization. Creating and delivering content based on a customer’s specific preferences is the best way for brands to build long-term relationships with their audiences. This means using data insights to deliver the best news to the best person at the best time.
Practical examples of data-driven innovation
So let’s take a look at some examples of data innovations where companies base their campaigns on their insights to achieve positive results:
- Spotify – The music streaming service created a campaign at the end of the year based on users’ listening habits. Ads contain lines based on data insights like “Dear person who played” Sorry “42 times on Valentine’s Day, what did you do?” and “Dear 3,749 people who streamed on the day of the Brexit vote,” It’s the end of the world as we know it, “stay tuned.” Using listener data, Spotify was able to create fun, unique ads, ever by region, and the positive effects were widespread as subscriptions hit a record high for the company when they were released last December.
- DirecTV – In search of new ways to connect with consumers who were not subscribed to a television schedule, DirecTV has focused on a specific market: new homeowners. With the collected data, they were able to address consumers who had recently requested a change of address. With this data, they then sent ads that led consumers to a personalized homepage that spoke directly to the “mover” segment of their website.
- Very – As the studies show 71% of people prefer ads that are tailored to them. The clothing company Very used the customer data it collected and went one step further by combining it with current weather information. This meant that they could recommend products that matched the weather at the customer’s location, such as: B. coats and hoodies in the rain or sunglasses in the sunshine. With this approach, Very was able to display 1.2 million variations of their banners and homepage, each operated with customer data.
- Abreva – As a company specializing in cold sore medication, Abreva wanted to reach a younger target group in terms of its current population. With this in mind, they decided to turn their attention to YouTube. Abreva’s marketing team used machine learning to identify and reach its target groups. They then created 119 versions of a base ad and adapted the copy to what a YouTube viewer saw. A teen who watched a celebrity gossip video saw a different ad than those who watched a makeup tutorial. This data-driven campaign enabled Abreva to increase overall ad recall by 41% and search interest among the target audience by 342%.
The future of data-driven innovation
A data driven digital marketing strategy should be a key aspect of your overall digital approach. Since data-driven innovations will be the focus of more and more strategies in the future, it is more important than ever that customer data is incorporated into your marketing. When data is used in conjunction with the appropriate technology, you have the opportunity to create powerful, creative campaigns that connect with your audience on a deeper, more authentic level. By understanding your customers and anticipating their needs, a data-driven strategy can offer marketing professionals an optimized way to stay connected with a target audience.
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