How Data-Driven Innovation Will Change in 2020

No longer is marketing reliant on assumptions and gut feeling alone. Today, data-driven innovations are how marketers are looking to operate. Data has the potential to be your most valuable marketing resource. With the right information in hand, you can create scalable and repeatable marketing processes. This is the true value of DDI as you can let your campaigns run based on data-driven innovation meaning you can focus on the creative side and optimize effectively.

What is Data Innovation?

Essentially, data-driven marketing is the strategy of using customer information for optimal and targeted messaging. The rising quality and quantity of marketing data has seen many companies begin to implement this approach for creative production and automation. Data-driven decision-making is the process of taking answers to questions like who, when, where, what message, and making them a part of your marketing strategy moving forward.

What Will Shape Data-Driven Innovation in 2020

In Europe, GDPR has already started to have an impact on how companies collect and use someone’s data. One of the major changes introduced by the GDPR is the requirement for organizations collecting personal data to obtain the informed consent of individuals as opposed to just implied consent, which was previously the case. Examples of this already taking effect are regarding the popups that appear on most websites asking you to tick a box agreeing to the use of cookies before receiving access to the site’s content.

However, in the USA, CCPA, effective January 1, 2020, will have a significant impact on corporate privacy initiatives across all sectors. Considered to be one of the strictest privacy laws in the United States, it provides California residents with the ability to control how businesses process their personal information. Businesses now have to honor requests from residents to access, delete, and opt-out of sharing or selling their information. Additionally, businesses will have to consider a number of CCPA-specific requirements when updating their privacy programs, such as opt-out measures and the need to stop selling consumer data upon request. In light of this, alongside 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 Innovation Will Change in 2020

Alongside factors like GDPR and CCPA, there will be several other examples of data-driven innovation trends in the coming year. Data-driven insights are continually evolving and are able to add value to businesses in ways that were not previously possible.

• As improvements in artificial intelligence and machine learning continue to occur at a rapid pace, it will allow companies to employ faster and more accurate ways of processing data at scale. Optimizing campaigns on the fly will become much easier as AI and machine learning capabilities continue to develop.
• Retargeting ads will grow in their usage. As consumers continually move between different platforms and devices, retargeting is becoming more and more important. In this case, a brand might use data-driven advertising to target someone who has moved on to other pages, reminding them of what they were looking at on their site. These can be especially useful when a customer abandons their cart, as the ad can help remind them of what they left behind and push them towards a checkout.
• Personalized marketing based on data will become more commonplace. With a data-first approach, marketers can build email marketing plans that deliver high levels of personalization to individual customers. Creating and delivering content based on a customer’s specific preferences is the best way for brands to build long-lasting relationships with their target audiences. This means using data insights to deliver the best message, to the best person, at the best time.

Real-Life Examples of Data-Driven Innovation

So let’s take a look at some examples of data innovations where companies built their campaigns around their insights to generate positive results:

• Spotify – The music streaming service crafted an end of year campaign based around their users listening habits. Ads included lines built around data insights such as ‘Dear person who played “Sorry” 42 times on Valentine’s Day, What did you do?’ and ‘Dear 3,749 people who streamed “It’s the End of the World As We Know It” the day of the Brexit vote, Hang in there.’ By using listener data, Spotify was able to craft funny, unique ads that could be localized based on area. The positive effects were widespread as subscriptions met a record high for the company upon their release last December.
• DirecTV – While looking for new ways to connect with consumers that were not signed up for a television plan, DirecTV honed in on one specific market: new homeowners. With this data collected, they were able to directly target consumers that had recently filed for a change of address. Using said data, they then sent advertisements that led consumers to a personalized homepage that spoke directly to the “mover” segment of their site.
• Very – As the studies show, 71% of people prefer ads that are tailored to them specifically. The clothing company Very used customer data they had collected and took it one step further by combining it with up-to-date weather information. This meant they were able to recommend products matching the weather in the customer’s location, say coats and hoodies when it was raining or sunglasses when the sun was shining. With this approach, Very were able to display 1.2 million variations of their banners and homepage, each fueled by customer data.
• Abreva – As a company specializing in cold-sore medication, Abreva wanted to reach a younger target audience in relation to their current demographic. With this in mind, they decided to focus their attention on YouTube. Abreva’s marketing team leveraged machine learning to identify and reach their target audiences. They then created 119 versions of one base ad, customizing the copy to match what a YouTube viewer was watching. So a teenager watching a celebrity gossip video saw a different ad to those who were watching a makeup tutorial. On the back of this data-driven campaign, Abreva drove a 41% lift in overall ad recall and a 342% lift in search interest among its target audience.

The Future of Data-Driven Innovation

A data-driven digital marketing strategy should be a key aspect to your overall digital approach. With the data-driven innovations set to be focal points of more and more strategies in the future, it’s more important than ever that customer data is incorporated into your marketing. When data is used in conjunction with the appropriate technology, it gives you the possibility to build 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 provide marketers with a streamlined way to stay connected with a target audience.