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5 ways to use data-driven advertising

Sophisticated marketing platforms have given us the power to gather data points that take the guesswork out of digital advertising. Availability of data, insights, and analytics has made it possible for marketers to make better media buying choices, reach out to the ideal target audience and craft a message that resonates and drives business outcomes.

The rise of big data and artificial intelligence has allowed the advertisers to develop ad campaigns that are helping them gain even deeper understanding of their target audience. But, for less mature advertises, it is important, to begin with the basics.

Here are 5 ways in which you can use data-driven advertising to improve outcomes today.

1. Retargeting

Retargeting is one of the many ways in which data is revolutionizing digital advertising. User data helps drive remarketing campaigns by capturing user’s online activity and behavior.

Whenever a user visits your website, the remarketing code (known as a pixel or tag) is triggered and a cookie file is stored in the user’s browser. When the user browses other websites, they will get to see relevant ads of your products through the ad platform.

Some people view remarketing as an invasive advertising strategy, but when done right, it can elevate the customer experience. For example, a CRM company might motivate MOFU (middle-of-the-funnel) leads to download an eBook. When a prospect downloads the ebook, the remarketing script is triggered. Now, a bad remarketing idea would be to promote ads that push the prospect to buy the product. A good remarketing strategy would be to invite them to sign-up for a free demo. This comes across as less intrusive and relates to the buying stage the prospect is in.

2. Programmatic Advertising

Traditional advertisers usually followed the “spray and pray” approach. Advertisers would spend lots of money to run their ad on TV or to display a banner ad in newspapers. The impact and ROI were difficult to calculate.

Enter programmatic advertising. Programmatic ads automate the space buying process by analyzing data to decide which ads to purchase and then bids for them in ‘real-time’ bids conducted via a digital exchange. In programmatic, advertisers target users based on user characteristics like demographics, geography, interests, behavior etc. without any human intervention.

The user data is stored in a platform known as data management platform (DMP). The DMP aggregates first and third party user data through various marketing efforts like PPC, social media, website, mobile apps etc. The third party data provides the clients an extensive range of data points to better understand their audiences. You can also purchase someone’s first-party data privately, and it is termed as second party data. Through demand-side platform (DSP), advertisers can automate the purchase various types of ads.

3. Predictive Advertising

Predictive analytics uses data, artificial intelligence and statistical algorithms to predict responses and outcomes. Predictive advertising uses the same principles of predictive analytics in the advertising context.

With the help of predictive advertising, you can identify a potential audience and reach out to them with highly targeted messaging on the right platforms. Artificial intelligence analyzes customer behavior, characteristics, past responses and purchases etc. with the help of statistical algorithms to anticipate future sales and responses.

For example, Facebook offers lookalike audience targeting which is derived from custom audiences. You can feed your customer list, website visitors, page likes to Facebook and based on their attributes, Facebook will prepare a list of users with similar attributes and behavior. Essentially, Facebook helps you reach a wider audience having similar attributes as your existing customers. Even though these potential audiences may not be familiar with your brand, they are more likely to become your customer since they look a lot like your existing customers.

4. Recommendation engines

Primarily used by e-commerce and online media streaming companies, recommendation engines predict user preferences and tweak website communication accordingly to maximize ROI. According to McKinsey & Company, Amazon generates 35% of it’s revenue through its recommendation engine. Recommendation systems are actively helping companies improve user experience because customers expect retailers to know what they need.

There are several approaches to building a recommendation system. Two of the most popular are:

  • Collaborative filtering: if person A likes product X and person B likes product X and Y, then person A might like product Y as well.
  • Content-based filtering:  instead of relying on user similarities, product characteristics are taken into consideration. So, if you are buying Dale Carnegie’s How to Win Friends and Influence People, you might also be suggested Stephen Covey’s 7 Habits of Highly Effective people due to a similar genre of the books.

5. Data Driven Search Engine Marketing

With more than 3.5 billion searches being performed daily exclusively on Google, marketers have heaps of data available at their disposal. But data alone will not make sense if you are not able to sort and find patterns to use it in your marketing. Major search engines have upgraded themselves based on search history, search intent queries, and language usage. With the help of tools like Google Trends and Google Keyword Planner, advertisers can find search trends; find out relevant keywords, keyword strategy used by competitors and find out patterns and how they have evolved over time. Based on this data, advertisers can identify the peak duration in which search and purchases are high and implement search marketing strategy accordingly. Search can be expensive but there is a method to the madness, and if handled strategically, you could end up scoring some valuable keywords for less.

There you have it. 5 ways you can use data to optimize your digital advertising efforts and improve your outcomes. Digital advertising has evolved dramatically from its early days, and starting with these 5 basics will ensure you set up a strong foundation for a future dominated by data-driven marketing.

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source: MTA