Targeting

If you reach more people than the planned target group, it’s a waste of your company’s energy and you will miss the mark. Since only a small per­cent­age of these users are in­ter­ested in your product, the scat­ter­ing and potential sales don’t correlate with each other. The dif­fer­ence between dis­tri­bu­tion and dis­per­sion is known as scat­ter­ing loss. It causes un­ne­ces­sary ad­vert­ising ex­pendit­ure. You should define a target group and analyse their data on visited pages, cross-topic pref­er­ences, and com­pet­it­ive keywords. Thus, im­ple­ment­ing your scat­ter­ing plan in a targeted manner.

Within an ad­vert­ising network, websites exchange data with each other in order to obtain the most accurate customer profile they possibly can. This is often done using browser cookies. The small files contain not only a website’s preferred settings in the re­spect­ive browser but also target group relevant customer data such as age, gender, region, purchase decisions, and search history. Network partners use the data from the cookies to place targeted ad­vert­ising on other network sites. Before you start a campaign, analyse your customer data and make sure you define your target group.

Ad­vert­ising networks such as Google AdSense, Amazon Part­ner­Net, and Facebook Audience Network impress third parties with a multitude of stat­ist­ic­al data. This is due to the fact that these operators are market leaders in their re­spect­ive fields (search engine, online trade, social media). Millions of users around the world provide personal in­form­a­tion, use the search function, and share their interests through likes. Ad­vert­isers configure their dis­tri­bu­tion planning based on these criteria. Ideally, users will then only see ads that interest them. For example, if you are looking for local bathing fa­cil­it­ies and have specified your re­la­tion­ship and whether you have children on Facebook, you may receive offers for family-friendly ac­com­mod­a­tion at the nearest lake or ads for beach toys. Why and how each user sees a specific banner depends on the re­spect­ive targeting method.

By ad­dress­ing the right target group, you the­or­et­ic­ally provide users with everything they need or could want. If you are also in direct contact with your customers e.g. via news­let­ter or social media, they will feel directly addressed and valued. This is how you build up a loyal customer base. In addition, the in­form­a­tion pool is growing, which helps you to an­ti­cip­ate your target group’s wishes.

However, the use of personal data has also been cri­ti­cised. On the one hand, people are becoming more and more sensitive when it comes to data pro­tec­tion. The idea of a 'trans­par­ent client' where there is a treasure trove of personal data that is analysed and evaluated (or misused) is no longer a fu­tur­ist­ic vision. That’s why, despite all the eagerness for per­son­al­ised ad­vert­ising, the security aspect cannot be ignored when customer data is at stake.

On the other hand, if you follow your customers every­where they go online it’s going to have the opposite effect. Potential customers might get irritated if they are con­fron­ted with per­son­al­ised ad­vert­ising every time they click on a new site. Some of them will delete their cookies. Frequency capping helps you to not go overboard with ads by reg­u­lat­ing how often they appear.

When gardeners plant turnips, they don’t just spread the seeds on the plot. They actually make ruts to keep a precise distance between the ve­get­ables and then plant the seeds one to two inches deep. Grass seed, on the other hand, is easily thrown on the soil and then kept watered. If these cul­tiv­a­tion methods were switched, neither the turnips, not the grass would grow. Similarly to this example, the result of a marketing campaign depends on customer demands and the targeting method chosen. You need to really think about your target group and combine the relevant targeting tactics. We have put the methods in two cat­egor­ies: technical targeting and user and en­vir­on­ment­al targeting.

The technical methods analyse at which times your target group uses the internet. They determine the location and the technical re­quire­ments. These methods enable you to reach your target audience when they are at their most receptive to ad­vert­ising. In addition, you can ensure that devices and browsers optimally display your ad­vert­ising material. The strategies that deal with users and your content rely on a detailed analysis of search queries and the ways your customers behave online. Only place ad­vert­ise­ments that users will find helpful or in­ter­est­ing.

When targeting, false drops (also known as 'false hits') occur. Common triggers include ambiguous terms (homonyms). If a keyword has more than one meaning, the display might appear in the wrong place. If users are looking for a com­bin­a­tion of 'Cancun' and 'swim', the search engine might suggest swimming lessons in local pools instead of the best beaches to visit to swim in the sea. Both terms belong to the topic of 'Cancun' but different users will expect different results when searching for these words.

Bigger problems occur when it comes to com­pletely ir­rel­ev­ant or det­ri­ment­al keywords. False drops like this harm the campaign because the keyword either appears in a negative context or addresses people outside the target group. These scat­ter­ing losses affect your budget. Therefore, check be­fore­hand whether your ad­vert­ise­ment could appear in the wrong context due to the keywords you’ve chosen.

In con­tex­tu­al targeting, banners also sometimes appear at un­suit­able times. We will use the Cancun travel package as an example. If you enter 'Cancun', 'flight', and 'travel' as keywords, your advert may appear in an article about a plane crashing at Cancun airport in 1977 since your keywords appear in the article. Readers could then associate your brand with the negative state­ments in the text. To refine the method, a semantic context analysis is possible.

Channel targeting seems to be a secure form of marketing. However, this method does not enable par­tic­u­larly precise targeting. Subpages often open up more defined topics, which is why more targeted marketing is possible. Channel targeting works with more roughly-defined cat­egor­ies. As the number of potential buyers in the group will be com­par­at­ively low, there will be some scat­ter­ing loss.

Even be­ha­vi­our­al targeting has its problems. Although a customer profile is created over time, ad­vert­isers do not access the in­form­a­tion until the user has left the website. Ad­vert­ise­ments follow users through the internet, even if they have already made a purchase or are now in­ter­ested in something else. This method’s timing shouldn’t be un­der­es­tim­ated. Pre­dict­ive be­ha­vi­our­al targeting goes one step further. This method expands in­form­a­tion about surfing behavior in order to carry out an immediate analysis on re­gis­tra­tions and survey results. Marketing al­gorithms use the resulting profiles to address customers directly on the site.