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When campaigns with third-party data pay off

In recent months, the keyword “big data” was the Holy Grail of sorts in the marketing realm. But until now, many discussions around the topic were primarily carried out at congresses and conferences in the more theoretical form of the Knights of the Round Table. This is especially so when it comes to external data (third-party data) which advertisers purchase in addition to their own data (first-party data), in order to control more targeted online campaigns.

This is because up until now, campaigns with third-party data only existed in the specialist lectures of most international advertising service providers, but unfortunately, had far too little presence in the German online advertising market. The infrastructure stemming from ad servers, data management, and demand-side platforms was available, but data suppliers were missing who could help a market to get off the ground.

But this situation is changing and more and more companies are also offering data for sale which is relevant to the German market. This provides a good reason for advertisers and their service providers to ask two central questions in particular:

  1. How much uplift is third-party data expected to supply to my campaign?
  2. With that in mind, how much might third-party data cost, in order to ensure that the campaign remains at least as efficient as it was before — and in an ideal case, even more efficiently?

The answer to the first question in particular is a difficult one, because, for one thing, “the ultimate campaign” does not exist. By the same token, as a general rule, advertisers have little to no empirical knowledge regarding the use of third-party data.

Therefore, I recommend that the question be asked differently and restated in terms of the second point below: If third-party data costs a specific amount, then how high must the uplift of the campaign be, in order that efficiency remains at least at the current level? And if the result is that there must be a minimum uplift of over 30%, then at such a point in time at the latest, an additional purchase of external data should be more closely scrutinised or all media alarm bells should ring.

In order not to surrender in advance, I thereby offer—without obligation and free of charge—my three rules of thumb which can be helpful in the use of third-party data in digital marketing.

1. Examine data quality very carefully!

Data offered from a supplier or data management platform must absolutely be put to the acid test before purchase. Enquire about how the data is labelled and if it really comes from the market in which it is to be later used.

Pay attention to how the data was generated: Is it “hard” data, or were projection algorithms used in the generation of data? If the data was originally collected in the offline world, it must also be examined as to whether the matching procedures conformed to data protection laws. And, last but not least, the question arises as to whether the specified quantity and granularity of the data profile is truly credible in relation to the total size of the target audience.

It is essential to consider in advance how you can analyse the quality of the purchased profiles. For example, measure the hit rate of the purported characteristics, e.g. via a panel or an online survey. Or, alternately, are there other measurable key values (KPIs) in the campaign which are to be improved by the data? If the answer to both questions is “no”, then steer clear of this data.

2. Choose the shortest path!

Campaigns that rely on third-party data can run into a quantity problem very easily. Why? Because the quantity of available profiles are generally less than the desired amount. This is particularly the case if the target audience is especially narrow and, at the same time, the data quality is expected to be high.

In order to explain why the quantity of available data is so important, a small technical digression is unavoidable: In the use of external data in a campaign, unfortunately, all acquired cookies are never obtained. This means: Some data sets are purchased, but cannot be used. This occurs, for example, when a portion of the cookies have been deleted by the users since then, or originate from another group of users, who are not in the environments in which attempts are made to find these users again.

This shrinkage is exacerbated by the fact that during the transfer of data from the supplier’s system to the buyer’s system, a synchronisation of cookies must take place over the user’s browser. Both systems must exchange their cookie IDs as well. The quantity of data is reduced considerably by means of this cookie synchronisation, because at some point, every user must be found on the website by the system for this purpose. Our experience shows: Even in the best-case scenario, about one-fifth of the available profiles are lost during this process. If the cookie synchronisation is poorly implemented, then very quickly, more than half of the profiles can be lost.

The risk of loss can be minimised by allowing the cookie synchronisation to occur as near as possible to the place that the data was generated or put online. Thus, all unnecessary partners within the supply chain are eliminated! These only cost money and reduce the quantity of usable data. In case the data supplier already employs a data management platform, the data can possibly be transferred directly into the delivery system, and in this way, you avoid an additional data synchronisation process.

3. Recalculate in advance!

A simple calculation can decide the fate of your data campaign: Set the price that you should pay for third-party data in accordance with the added value that you must achieve by the use of external data. Do data costs eat up the performance improvement that the campaign is meant to achieve? In this case, the use of third-party data would not improve the campaign’s efficiency. If you still have no empirical knowledge as to whether the uplift that must be generated by the data is realistic, then ask experts who can present you with benchmark variables.

In the purchasing of third-party data, take profile quantities and target audience sizes into account. The acquisition of data does not always pay off. Thousands of users that were, for example, identified as clear-cut interested parties for an especially strong-smelling type of stockfish might be a valuable target audience. However, it is rather unlikely that it is worthwhile to address these people though a narrowly focused re-targeting with a display campaign. Here, it would be better to search for other, more cost-efficient methods of reaching these fish aficionados.

Whether the use of external data in online marketing is worthwhile can generally only be assessed by companies in retrospect. However, it does not hurt to carry out a few simple calculations in advance. At any rate, the hardest currency is the experience gleaned with the performance values of campaigns. Wherever suppliers of third-party data can provide satisfaction—both when it comes to the quality of data as well as the price—then they have a rather good chance to belong to the Round Table of advertisers in the future.

First published in German by internetworld.de.

Five tips for integrated Google Shopping Campaigns

The step was not unexpected, but its consequences are nevertheless striking. For a few days now, the Google search engine is no longer showing paid AdWords ads to the right of search results. Google made this change as part of its endeavors to adapt search results to mobile devices, departing from the classic desktop experience.

The conversion substantially squeezes the ad space available for advertisers. It reduces the overall available count from up to ten text ads across the entire page to a mere three positions above the search results. According to Google’s announcement of the changes, only “highly commercial” queries will be given a fourth central spot. The move will increase competition for the remaining positions, so customers and agencies must expect higher CPCs and thus more expensive AdWords.

Stronger in the focus of digital marketing planning

To cope with the intensifying competition for Google AdWords, it is worthwhile to take a fresh look at Google Shopping. Unlike AdWords, the image-supported ads do stay in the right-hand column and thus become more prominent from the point of view of digital marketing.

This makes it an advertising format with many advantages. Finally, there is hardly a channel as goal-oriented and platform-independent in its approach to users such as Google Shopping ads. Not only do Google Shopping’s graphical results visually stand out in comparison to classic text ads, their usage is continuously increasing as well. According to a 2014 study by the advertising technology company Marin, more than 30% of all ads in the retail sector were placed through Google Shopping, with more than 45% of Google Shopping clicks coming from mobile devices.

Optimize product data towards a targeted customer approach

However, the success of a Google Shopping campaign is not sure-fire. For best results, various disciplines of online marketing must work in synergy. To permanently achieve high click-through rates at the top of search results, you should optimize all product data for a targeted sales approach and provide them through platform-specific data feeds.

In addition, smart bid management makes all the difference when you want to get the maximum return on investment (ROI). In general, you need to consider the following five aspects:

1. Feed relevance
All information relevant to an ad is sent to Google via the data feed. It might need to be changed more or less often depending on the industry — for example, if the price changes or specific product versions are sold out. It is important that the data sent in the feed to Google Shopping stays up-to-date at all times. You must ensure round-the-clock monitoring of data feeds to avoid downtime and to be able to update prices and offers quickly and smoothly. The goal must be to have context-specific offers displayed to potential customers at any time and in any place.

2. Feed content
The integrity of the feed is just as important as its relevance. In this context, all product specifications defined in a Google Shopping feed must contain all relevant product information, such as its description, availability, price, or category. This applies in particular to optional configurations. Such custom data feed columns are used, for example, for top-performing products, brands, or to introduce other meaningful criteria to optimize the campaign. Product texts and descriptions must be analysed and published based on actual user search behaviour. This step is crucial to enable the tracking of ad visibility and shop purchases. Finally, high-quality pictures top off a positive user experience.

3. Keyword control
Advertising campaigns are controlled based on product information. In doing so, Google analyses behavioural signals to decide whether a particular product fits a query: If a product is especially often clicked in combination with a certain request, Google gives such ad a higher priority. But high click-through rates do not always mean high margins. Thus, it is better to have a product displayed when it leads not only to a click-through but also an actual sale. By properly controlling the keywords you can make it so that a data feed-based ad is preferably displayed when the product is searched in combination with its own brand. Here, the conversion rates are generally higher than those of organic entries or text ads without product images.

4. Reviews
64% of all E-commerce users state that product reviews are among the top two criteria in making a decision to buy. For women, this value is even higher, reaching up to 70%. In Google Shopping, you can configure the integration of product reviews graphically and in close connection to ad content. Good usability on smartphones and tablets maximizes the user’s awareness of and attention to product reviews, bringing them much closer to an actual transaction.

5. Bid management
As Google Shopping campaigns often generate a large part of sales in the long tail, it is essential that you use technology to recognize and analyse patterns in the bulk of individual values. Based on these findings you can not only optimize daily budget allocations and bidding strategies, but also forecast upcoming developments and seasonal trends by analysing recurring behaviour patterns. Furthermore, in order to control the campaign’s budget in a more efficient way, it is advisable to separate branded keywords, generic search queries, and, where appropriate, product-related keywords.

Bottom line

On the way to a data-driven marketing, one that focuses on compelling, cross-platform user experience, Google Shopping should be a staple in any marketing mix, as it is currently the most efficient and wide-ranging advertising channel. But from creation to delivery to reporting, this requires a complex process that takes into account a lot of different aspects. If such a process is in place, Google Shopping ads can also yield exceptionally high click-through and conversion rates. The effort is worthwhile.