Campaign Analysis

 This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

I’m increasingly convinced that the issues that most businesses face around the successful deployment of analytics in their business are not to do with their technologies but to do with their businesses processes. That view was reinforced this week when I was running a workshop with a group of students studying on a Masters Programme in Internet Retailing. Read more…

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

When it comes to online campaign tracking there’s a new buzz phrase in town: “attribution management”. In our business you know where’s a trend when you get asked the same question twice in the same week and at the moment the question seems to be: “How do I attribute sales to different marketing channels in a more sophisticated way?” Increasingly advertisers know that the way they are currently tracking campaigns and their return on marketing investment is sub-optimal. They know that the current paradigm of “last click or impression gets the sale” means that they are potentially making poor decisions when it comes to fully evaluating the role of different online media in the marketing mix. There is the classic phrase in marketing: “I know that half my advertising spend is wasted, I just don’t know which half”. In the online era of almost total accountability, it seems that we are still struggling with this fundamental paradox.

The problem is simple. In the majority of cases, online advertisers use their campaign management systems or their web analytic systems to determine how they attribute sales (or other conversion events) to different online marketing channels. The current paradigm is that the channel that delivers the last click or the last impression before the visitor converts gets credited with the sale. If someone sees a banner ad, then does a search, clicks on a sponsored ad and then visits the website and converts, the investment in the sponsored search link gets the full credit for the conversion.

So, on those results you may take the view to reduce the investment in banner advertising and increase the investment in search marketing as that’s the channel that seems to be getting results. That’s all very well and good, but what about the fact that the customer saw a number of banner ads over a period of time which raises their awareness of the brand and prompted them to be more susceptible to clicking on the sponsored link when they carried out a search. The two different media channels are doing a different job; one is raising awareness and consideration, the other is generating a direct response. But only the direct response mechanism is being credited with the “sale”. The danger is that you then turn off the investment in banner and display advertising because it doesn’t seem to be doing anything and the next thing that you notice is that the number of search generated conversions seems to be going down. We live in a multi-channel, multi-media world and we can’t manage these things in silos.

The solution is a touch more problematic. I think the key thing for advertisers to recognise is that the current paradigm is sub-optimal. Whilst they may be focussing their efforts on optimising their marketing investment within a channel through, say sophisticated bid management strategies, they may not be optimising their investment across channels because they do not have complete visibility on the dependencies of one channel on another.

The next question is then how does an advertiser recognise and quantify the indirect effects of some channels? The major challenge here is that many of the common technologies used in campaign tracking and analysis are not up to the task. The default setting for is generally to credit the last click or impression with the conversion event. In some cases it is possible with adserving technologies to look at the “halo” effects of display advertising on search activity but this is not a standard report and requires that the display and search campaigns are managed from the same tool. In some web analytic systems it is possible to define some basic attribution rules other than “last click wins” such as the ability to spread the credit across all channels that a visitor touches before they buy. However, as we’ve discussed before web analytic systems cannot take into account impression effects of display advertising.

According to a recent report by Jupiter on this issue (Next-Generation Response: Effectively Managing Attribution) the solution for an advertisier appears to be to turn to their advertising agencies. Some agencies have developed their own analytic systems that operate off the adserving data. These systems allow for more flexible and sophisticated attribution management but lock the advertiser into a specific approach. An alternative might be to bring the data in-house but that requires the advertiser to handle and manipulate large volumes of data that they may not be very comfortable with. Another possibility is to use a third party to collect, manage and report on the data on your behalf.

They say that recognising a problem is half way to a solution. When it comes to attribution management, the trend is that advertisers are realising that the decisions they are making on the basis of the data they have might be less than perfect. The challenge they face is that the solutions at the moment are somewhat limited. Hopefully we will see the technology providers in the adserving, campaign management and web analytics space working to provide better ways of understanding the complexities of the online marketing mix.

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

In this series I have been taking a look at some of the issues and challenges in tracking the effectiveness of online marketing campaigns. More and more advertisers are looking to improve the way that they track their campaigns so that they can make smarter decisions about the way they spend their money.

One of the challenges is that quite often they are using multiple systems to manage and track their campaigns. Advertisers or their agencies will be using adservers, bid management tools, email systems and so on. In addition, they may be tracking their campaigns using their web analytics system. One of the common issues raised is that the data from the campaign management tools is often different to the data from the web analytics systems and so one of them “must be wrong”. The thing to realise is that the different systems are generally measuring different things and so the numbers are quite likely to be different. So it’s important to be clear about what is being measured and how it’s being measured.

So first of all, what’s being measured where? In general terms, campaign management systems such as ad-servers and bid management systems are measuring impressions and clicks, ie how many times the ad was served and how many times it was clicked on. Web analytics systems measure visits, ie the arrival of a visitor on a website. One of the biggest areas of discrepancy is between the number of clicks recorded and the number of visits observed from a particular campaign or channel. There might be a number of reasons for this.

First of all, clicks and visits are not the same thing. Someone clicking on an ad is not the same thing as someone being recorded as landing on a website. There are three main possibilities why this might be so.

1. The person doesn’t actually get to the website
2. The person gets to the website but moves on before the visit is recorded
3. The person gets to the website but is not recognised as coming from the campaign

In the first instance someone clicking on an ad may never reach the website. This might be for a number of reasons but can occur if the website doesn’t load quickly enough. They click the ad, wait and then go back to the search results page, for example, and click on another ad.

In the second instance the visitor might land on the landing page but move on further into the site or off the site before the landing page visit is recorded. Most web analytic systems used for campaign tracking will be using a page tag to capture the data. If the visitor lands on the landing page and then either clicks through to another page or exits the site before the tag is loaded, then visit won’t be recorded against that campaign. Quite often the tag is placed towards the bottom of the page and so if the page loads slowly or the visitor doesn’t wait for the page to be loaded, then it’s possible that the tag won’t load.

In the third instance, the visitor gets to the website, the visit is recorded, but it’s not attributed to the particular campaign. One of most common methods of tracking campaigns using a web analytics system is by attaching a campaign tracking parameter to the URL of the landing page. It might look something like this: “www.mysite.com/landingpage.html?source=google”. In this case the “source=google” bit identifies that visitor as having originated from a Google Adwords campaign. All the main web analytics systems can be configured to recognise and report on campaigns in this way. The configuration varies from system to system but the principle is the same, and if the tracking parameter is missing then the visit won’t be recognised as coming from a particular campaign.

Creating the camping tracking parameters and attaching them to the landing page URLs is often a manual or semi-automated process. This means there is always the potential for error. Advertisers need to develop and implement appropriate business processes to ensure that the right campaign tracking parameters are attached to the landing page URLs for all their ads. This can be quite a challenge, particularly if have you have a number of different agencies managing different aspects of your campaigns. But with campaign tracking it really is a case of garbage in, garbage out. If the campaign tracking parameters are not correct, you won’t get good data in your reports.

Another thing to look out for is the impact of using redirects. Some campaign management systems might intercept and redirect the visitor between the ad and the site. They do this so that they can record the ad being clicked in their own system. What advertises need to be careful about it whether the redirect has any effect on the campaign tracking parameter and that the parameter remains attached during the redirect process. It’s another thing that needs testing and checking.

A big difference between campaign management systems and web analytic systems is that web analytic systems only track click-throughs and the subsequent behaviour. Campaign management systems can also measure impression levels and, in the case of ad-serving technologies, can also track subsequent conversion events. I discussed the issue of measuring post-impression or view-through effects in the last column but it can be a major source of discrepancy between what a campaign management system is reporting and what the web analytics system is reporting. Particularly as the conversion might be attributed to one channel in one system and to another channel in another system. This whole area of what is called “attribution management” is something that I will look at next time.

Till then…

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

Last time I started to look at the knotty problem of campaign tracking. Since the birth of offline marketing we have been using simplistic views of how campaigns work and which channels produce results and which channels don’t. The classic approach is that the “last click gets the sale”. In other words the channel or campaign that generated the last visit before the conversion event gets the credit for that conversion. When the internet was viewed purely as a direct response medium and campaign plans were simple, this approach might have been sufficient. But in today’s multi-channel, marketing mix optimisation world, this approach is naive.

One of the main problems here is the technology landscape that most advertisers are faced with. First of all there are a number of different systems involved. Each marketing channel will tend to have its own system for the deployment and management of marketing activities. For example, advertisers use bid management systems for PPC (Pay Per Click) search campaigns, an ad-serving systems for display ads, an email system for managing emails and so on. They may be using these tools in house or an agency may be using them on their behalf.

Each of these marketing systems will have its own data capture and reporting capabilities built in. This is important so that the channel activity can be optimised against the performance of the campaign in terms of clicks to the site and/or conversions. But it also means that whilst campaigns can be optimised within a channel (ie PPC search) it is difficult to optimise campaigns across channels because the data is sitting in different places. One of key issues then is to be able to get all the campaign response data in one place. The options here are to use a single campaign management tool across all channels or to collect all your campaign response data in one place, like your web analytics system. One you have all the data in one place you can then at least begin to look at optimising campaigns across the different channels that you use.

Campaign management tools like Doubleclick and Atlas can increasingly be used for multiple channels. Although originally developed as ad-serving technologies, they have expanded their capabilities by adding on bid management capabilities. It is also possible to track activities on other channels either through redirects or through the universal tags that are beginning to appear such as Doubleclick’s Floodlight tag. One of the advantages of the ad-serving technologies is that they can measure “post impression” effects of display advertising as opposed to just click-throughs.

Post-impression effects are where someone is served an ad impression on a site but they don’t click through. The ad impression is recorded and if that person subsequently arrives on the advertisers site, within a certain period of time, and converts, then that conversion can be attribution to the “post-impression” effect of that advertising.

For some advertisers the ability to understand post-impression effects is very important, particularly for branding campaigns. However, there are a number of issues to take on board about measuring these post-impression effects or “viewthroughs” as they are also known. First of all, advertisers need to ensure that the post-impression data is also discounted against marketing channels. For example, post-impression effects of display advertising need to be discounted against search activity. If display advertising drives increased search activity, then there is a risk of double counting the sales effect if the two channels are measured and analysed independently. This comes back to the issue of having the campaign data in a single repository.

The second issue about measuring post-impression effects is what time window after the ad has been served do you allow for the visitor to come to the site? The point of measuring post-impression effects is that ads do not always generate a direct response and that (in a similar way to TV ads) exposure to display ads build awareness and consideration which indirectly leads to conversion. But what time interval should you allow between exposure to the ad and a sale to say that there has been an effect? Although it does vary, typically advertisers or their agencies might use a window of up to 30 days. So, they are potentially attributing conversions to the fact that a visitor was served an ad up to 30 days earlier.

I think that advertisers need to consider the difference between association and correlation when evaluating post-impression effects, particularly for large brands running large campaigns. In determining the effects of marketing activity we are looking for correlation. We are looking for cause and effect. Just because someone was on a page where my ad was displayed and then they came to my site up to 30 days later, I can’t be confident that there is real correlation. It may just be a coincidence. However, if they saw my ad 5 times and then came to the site a couple of days later, I can be more confident that I am seeing some sort of real effect.

Next time I’ll be taking a look at the differences in measuring campaigns using campaign management tools and web analytics tools why they won’t necessarily be telling you the same thing. Till then…

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

One of the challenges that any business that does any level of online marketing these days is the proliferation in systems and data that they will be using. Typically an organisation or their agencies will be using ad-serving systems, bid management systems, affiliate management systems, email marketing systems and so on.

Each of these marketing systems will have reporting capabilities built in, with the data being fed by a tag on the key pages on the site. Often if a conversion event happens within a certain period (say 30 days) after someone has clicked through from an ad, an affiliate link, an email link or whatever the system Additionally they will be using a web analytics system to track campaigns too, usually by using tags across the site. As well as all of that they may be looking at customer acquisition data in their customer databases.

Today’s online marketers are not short of numbers. The trouble is when you have two watches, you’re never sure of the right time. The situation raises a number of issues such as:

• How do I mange all the different tags that I have on the key pages on my site?
• If I have all these different sources reporting conversions up to 30 days later how do I know which channel is really responsible for the conversion?
• How do I best attribute conversion effects to the effect of different types of online marketing working together?
• How do I reconcile all these different data sources?

These are not easy questions to answer but at least the technologies are moving in the right direction. Take for example the development of what are known as “universal tags”. The idea of these universal tags is that they alleviate the need to have separate tags on your key pages for each tracking system that you use. In theory the universal tag sends the right system the right information at the right time. This technology is still in its nearly days and a number of different providers of tracking technologies are competing in this space.

A more common concern amongst organisations I work with is about how sales or other conversion events are attributed to different marketing channels. The scenario is this: a visitor clicks through to the site from an affiliate link one day but doesn’t convert. The next day the same visitor does a search and clicks through to the site and converts from a sponsored link. Both the affiliate tracking system and the bid management system will be configured to count sales up to 30 days later and so in this case both will “claim” the sale.

The trouble is that the online marketer doesn’t know which channel is really driving the conversions and the sale will be counted twice. Even worse it may be paid for twice if the channels are operating on a CPA (Cost per Acquisition) type of deal. The key thing here is to get to a point where a single tracking system is responsible for attributing conversion events to campaigns based on some criteria.

The use of the universal tags discussed earlier can help this situation but also many organisations use their web analytics systems to provide that single point of reference. The web analytic tools can be configured to recognise visitors that arrive from different campaigns and in the event of a conversion, assigning that conversion to a particular marketing channel or campaign.

However, web analytics solutions don’t provide the total answer for a couple, of reasons. First of all they only track “click” events and secondly the way that attribute the conversion to a channel, or campaign is often relatively simplistic. Depending on the goals on a campaign and the process by which awareness is built and converted into a conversion event, the view of campaigns that you get from a web analytics tool may not be providing the right perspective on which decisions about marketing optimisation can be made.

Next time I’ll take a look at some of these issues in more detail. Till then…