Everything you need to know about digital marketing

  1. Targeting & Retargeting
  2. Video versus Images
  3. Engagement Measurement
  4. Machine Learning and Software

Targeting & Retargeting

Targeting is when you use tools like Facebook Business ads or Google AdWords to target an audience for you advertisement. Typically you will target your audience based on interests and likes from social media along with specific behavioral patterns Google or Facebook has tracked and identified. Once you create this audience you can market to them with various promotions again and again by saving the audience in the respective ad platforms.

Retargeting is when you are retargeting a consumer based on them seeing one of your ads or even just visiting your website once or twice. Retargeting can be leveraged at a very granular level with more data points from previous advertisements. For example, if you recently ran a video ad on Facebook, you could target consumers who watched the video past a certain point. This allows for the refinement of your audience. Using this technique digital marketers can curate a small subset audience that is highly likely to convert. This is known as a honey pot.

Video vs. Images

Video and Imagery both have their place in marketing. Some cases call for quick graphic display with no load time and images work great for that. However bandwidth is increasing tremendously and the speed of mobile devices is up to par with desktop speeds on most networks. The time is right and the web is going video.

Video allows you to monitor various points in the video where uses take action. This action could be an opt-in it could be a close button or anything else. You can gauge what parts of your video work and which parts don’t. You can even determine how long the attention of the consumer you have for the next video.

With an image, on the other hand, you have very little data and have to only speculate on what worked or didn’t. Keep things fresh and use video when possible especially for ads. Don’t throw images out just yet though as they have their place in marketing as well.

Engagement Measurement

Engagement measurement is when the hard work comes into play for digital marketeers. To be effective they have to measure all the data points to find the most valuable engagements with their content and begin catering to the trend to refine their marketing strategy.

Previously I mentioned measuring the engagement measurement of a video Ad running on Facebook Ads or Google AdWords. Think of engagement measurement as a combination of data points from previous ad cycles extrapolated into an intuitive format like a chart or a report.

At it’s most basic level you may have encountered this when running Ads on Facebook or Instagram. On each post you “boost” it displays verticals on engagement. This is very insightful because it shows you what content is working and what content is not working when you are running a campaign.

Machine Learning & Software

Machine Learning & Software have come a long way. Big data systems like IBM’s Watson system are becoming available at scale to the masses. Software systems now have access to troves of consumer data which in the right code can translate into marketing automation and efficiency.

Typically this is conducted using machine learning algorithms. Data is consumed by the software from various sources like Facebook, Google, Amazon, Instagram, and other data sources. This data is then analyzed for patterns and trends and sorted into intuitive metrics that can be read by real humans. This process is one form of machine learning. The algorithm dictates how the input data is processed. An algorithm is just a series of steps to achieve the desired outcome. Marketing agencies that are using systems like these often tailor their own business logic and outsource the development of the software and algorithms.