Despite the sunsetting of third-party cookies, digital marketers still have a wealth of data to inform their strategy. The difficulty starts when advertisers have to choose which dataset to base their decisions on.

Marketers can create high-definition profiles of their target audiences and apply focused targeting tactics. However, in many cases, the assumptions they make about their audiences are skewed by personal perceptions or misinformed by past sales data. In fact, in today’s volatile world, analytics that rely on past user behavior are not always a good predictor. Instead, focusing on the objective predisposition of certain audience segments towards advertised products can yield much higher returns.

To help advertisers make better decisions, MGID is opening its internal findings to the general public.

What targeting strategy works best?

Contextual advertising has lately gained a lot of popularity since it does not rely on cookies and will not be affected by the looming third-party cookie apocalypse. On the other hand, interest-based targeting offers insights into user behavior and intent. In many cases, doing both makes sense. However, it is advised that advertisers direct their resources and focus on one strategy in order to maximize ROI.

Contextual advertising is relatively easy to conduct. An AI crawler recognizes the webpage semantics that best matches your ad, so for example, a home fitness equipment ad is served next to a diet recipe. This type of targeting allows advertisers to capture the users’ attention at the exact moment when they are browsing relevant content.

Targeting interest-based audiences at scale is more intricate and usually requires collaboration with third-party data providers (typically DMPs). One advantage, however, is that it allows advertisers to tap into users that displayed actual interest in these or similar products in the past.

Our study of contextual vs. interest targeting

To compare the effectiveness of these targeting tactics, MGID conducted an analysis of campaigns in the Healthy Living vertical that applied both targeting methods. Brands operating in this niche include fitness and exercise products, nutrition supplements, weight loss products, alternative medicine, muscle building and smoking cessation products.

The study covered 9 campaigns advertising brands in the Healthy Living category in Europe. In this experiment, MGID compared the impact of ad targeting strategy on the campaign’s reach and conversions. The study design was multi-cell RCT (Randomized Control Experiment), a methodology borrowed by marketers from the medical sciences to ensure that the essential variables are controlled for.

What metrics help us estimate effectiveness?

Most advertisers will not be interested in reach itself but rather in ad spend vs. conversions. To understand the ROI, ad performance is essential. For this analysis, eCTR (Expected Click Through Rate) and eCPM (Effective Cost per Mille, i.e., revenue effectively generated for every 1,000 impressions) were selected as the most relevant metrics.


eCTR, the projected probability that the ad will be clicked on (irrespective of position or other external factors) helps an ad rank high enough to be shown in a visible position. eCPM, on the other hand, shows the effectiveness of a campaign in real numbers. If CPM is the buying model, eCPM is the actual spend metric.

Obviously, from the advertisers’ standpoint, eCTR should be high and eCPM should be low. But if the data is conflicting, as in the table below, what metrics do you use to inform your decision?

The answer is generally CPL. The cost per lead is a straightforward assessment of the price incurred for acquiring a lead, i.e., a potential customer that needs further nurturing before buying. Which, in fact, is the case for virtually all internet purchases.


In analyzing the data of the 9 campaigns, MGID extracted three main findings, reflected in the summary table and further discussed below.

Scalable reach matters

The findings suggest that both targeting methods can deliver scalable reach. On average, campaign reach was higher for interest-based campaigns (+18%) as compared to contextual campaigns. When focusing on reach alone, interest-based targeting makes sense. When focusing on ROI and conversions, this metric is only the beginning of the equation.

Do not over-restrict your audiences

On one key issue, however, MGID’s recommendation concurs with Meta’s conclusion after a similar analysis conducted in the CPG vertical: advertisers need to choose one targeting approach. This is a case where failing to focus might be detrimental. In most cases, intersecting the contextual and interest-based targeting methods could narrow the audience and significantly limit reach.

Cost per conversion is king

The analysis found that even though interest targeting provided a broader reach, contextual targeting is more likely to be a winning strategy and deliver cost-efficient outcomes, at 8 times lower the cost per conversion.

Before choosing a targeting method, advertisers should critically assess the ability of the audience to drive higher impact (bring more conversions) and if their desired method reduces reach or increases eCPM.

Key takeaways

While summing up the findings in the category Healthy Living, three main points stand out.

Provide sufficient reach. In an attempt to zero in on campaign reach and ROI, do not overly narrow your audience. Sufficient reach is a requisite but not the only one; once you have it covered, move on to the next consideration.

If reach is remotely comparable, double down on cost. Compare the reach and cost trade-offs between targeting methods; if both interest and contextual targeting offer enough reach, do the math indicated above and choose the most cost-effective method.

Always experiment. Not only are the markets volatile but also are the shoppers — and increasingly so, too. Do not rely on one strategy. There is volatility inside verticals, geographies and segments — in addition to the instability that timing can affect all these components. You need to constantly test new approaches and compare results — even in adjacent or irrelevant contexts.

Advertisers should constantly evaluate the reach and conversion costs of different targeting methods, then choose and adjust targeting strategies based on their objectives. Marketing is not mathematics: if you change the context, 2+2 almost never equals 4. In effect, it is more like cooking: one ingredient influences another and you always need to keep an eye on the stove.