The framework classifies individual marketing activity, from high-level channels down to low-level keywords, with specific recommendations associated with each. One visualization of Logan Tod’s process looks a little like this:

So, if you can work out how much money you spent on any particular ad channel and how much revenue it generated, you can figure out just what to do next. But, identifying the latter is incredibly difficult. That’s why Adrian Nash, Head of Analytics and Insight at Logan Tod, welcomes the opportunity to work on clients with TagMan.

Speaking at TagMan’s second client event, TagMeet 2, Nash told the assembled throng: “Whenever a client says they have TagMan, I always say ‘great’ because it provides a great data source for us to work on.”

TagMan data enables Logan Tod to see how much revenue any online channel contributed to, not just in terms of being the last click, but throughout a customer’s path to conversion. This means a channel’s revenue contribution can be assessed much more fairly, particularly those channels that tend to be more effective ‘upstream’ of the last click.

But, the level of complexity that Logan Tod is applying to understand, report and recommend based on this kind of reporting boggles the mind.

Nash combined sweeping insight such as “it is better to be precise than accurate” (because precision is repeatable) with ultra-practical advice. For example, he explained that the path-to-conversion data in some tools doesn’t report anything over 30 days from the last click, which, based on recent Google research, indicates that up to 30% of research behaviour prior to a sale may be missed; “in those cases the first click isn’t the first click at all, it’s actually in the middle”.

He then explained how Logan Tod produces complex scorecards to rate the effectiveness of channels and applies predictive models to test how different mixes would affect return on ad spend.

In all, Nash’s session showed the level of expertise that can be applied to the data TagMan provides. However, using attribution data, Logan Tod recommends clients start with something simple:

Since using TagMan data makes it very simple to value every channel’s revenue contribution as first touch or last touch, advertisers can ask new questions of their marketing strategy and campaigns. If activity tends to appear only as the last touch before a conversion and doesn’t play a role further up the conversion path – is it’s role being overvalued or vice versa? TagMan data contains the information required to perform simple analysis like this through to more complex attribution modelling and ensures that there is a very low barrier to entry for clients wishing to use attribution to improve the performance of their marketing.

Speaking at TagMan’s most recent client get together TagMeet 2, Silsbury said: “It’s going to be a pig of a year.” And none of the other retailers in the room looked ready to disagree.

So what does Glasses Direct plan to do about it? Given its focus is online, then drive its online channels hard. Efficiency is the overriding mission. But, that doesn’t mean the company isn’t prepared to invest to get as lean as possible. Silsbury has a couple of things in mind:

1. Data unity: Getting all his marketing data in one place so he can learn to optimise his spend against entire user journeys, not channel-by-channel
2. Conversion: Maximising things like site speed to make sure that any customers that do get to his website, buy – and buy big – before they leave

Both these causes are part of his justification for implementing TagMan at Glasses Direct. The system will be used to enable Silsbury and his team, including long-time TagMan user Oli Elliott – formerly of online clothes retailer Boden – to track the entire online path to conversion of customers and attribute credit for sales much more fairly across the channels that made a contribution.

Silsbury is also one of the first to use TagMan v3, the newest version of the software, which includes several world-first features to lighten the load that tracking tags place on websites, and speed up his website. Silsbury said initial tests showed a 25-28% decrease in page load speed.

“We are obsessed with site speed,” he said. “Apart from the obvious impact on user experience and site conversion, it is part of how Google ranks your website.”

Silsbury has committed to TagMan for other reasons too. He explained how “tagging is an unnecessary distraction” that hampers his team’s ability to implement new technologies and campaigns. Tag management enables them to focus on the things that matter.

But, the biggest challenge is attribution. Silsbury is keen to distinguish the use of attribution tools for understanding user journeys better and for optimising campaigns.

He explained: “For me it’s important to distinguish attribution from optimisation. We mainly use TagMan’s attribution data for reporting, but we want to optimise paths-to-conversion, not individual channels so we use ‘assisted views’ [reporting that shows when a channel appeared anywhere in a user’s journey to a sale] to optimise. The Unique User ID assigned in the system enables us to see any user’s complete path to conversion and so see how all channels work together. It’s important to know that investment in one channel may see the conversion take place in a completely different one.”

Silsbury stated that in reverse to the above, there are very real financial efficiencies to focus on too and attribution should be used to deduplicate and ensure that you are paying the right party for its part in a sale. Using email and affiliates as an example, Silsbury’s argument is that if a customer has been sent a Glasses Direct email, then they can’t be considered a customer 100% driven by the banner they clicked on [up to] 30 days earlier. He wants to focus affiliates on customer acquisition and therefore not pay 100% where email is present in the path. Silsbury was quick to add though that “this is not a money saving tactic, more a way of reinvesting the saving in areas like paid placements, which do deliver genuine value from the affiliate space.”

Silsbury closed by stating that the ultimate goal is “getting to a fractional model, where split percentages can be applied to individual channels dependent on their importance in the path.”

“Ultimately it is a question of understanding, as Oli puts it, the ‘golden combinations’ that drive sales. We’re not there yet, but we’re getting there.”

Much of the gap between translating one into the other should obviously be filled by the client and their agencies, but that is only one part of the issue.

Too many companies I’ve spoken with use attribution to report marketing performance (rather than the old fashioned last click), but hardly any – unlike our clients – have made changes to their digital strategy or automatically optimised their spend as a result.

This is because these attribution tools have fallen into the trap of web analytics 5 years ago.  They are producing increasingly attractive graphics showing all sorts of interesting things, but none of them actually tell you what to do and what to change for the better.

The key to attribution change is two-fold:

1. Get tags managed: Marketing campaigns need to be not only reported by attribution, but also awarded credit/commission by the same model.  Email, affiliates, PPC, display and other managed channels all have their own technology to execute them, each with their own tracking (using pixels fired on the confirmation page); therefore you must use a tag management system which can conditionally fire a pixel (or part of it) so each channel sees the true value you are assigning to it.  In doing this, you will instantly deduplicate affiliates – not just against other networks but all other activity that you’re engaged in. If you pay on a last click model and SEO actually delivered the last click, then the credit should go to natural search. This is true deduplication and it motivates partners to focus on driving towards the goals you set them not to get a cookie on every converting customer.

2. Drag insight from data: Expertise must be applied to interpret the data and help you arrive at conclusions.  TagMan account teams constantly delve into client data to demonstrate its value through actionable insight but this is not their day job and there are people much more able and willing to take it on. That is why we have so many analytical partners such as Logan Tod, Data Science, Greenlight, Infectious and Latitude who have an insights team to analyse the raw data and go much further than pre-canned reports.

When tag management and insight brands at last make real inroads to driving effectiveness across their entire media mix – and that is the whole point of attribution.

Shanti Shunn, Director of Online Marketing at Harry and David

Shanti Shunn, director of online marketing at Harry and David, discusses why e-commerce sites need tag management, how tag management has evolved, and how to select a tag management vendor.

When and why did you decide you needed tag management?

At Harry and David we’re in all the multichannel markets, we have a lot of third-party tags on our site that relate to tracking and/or CPA payouts. I built my first tag management about 10 years ago, back when it was still called pixel wrapping. You had people who would touch multiple channels and check out, and you’d have multiple third-party tags firing. Based on them touching multiple channels, you’ve reported that order to multiple vendors.  And of course you’re reporting 100% of the order, so you have three different vendors who show the order as one of theirs.

It came down to attribution and at the same time order tallies based on the last channel touch. You don’t always want to optimize to that, but you want to facilitate the visibility.

So if you have multiple CPA vendors you’re reporting a percent of that order out, so you report that same $100 order to three CPA vendors and one’s 5%, one’s 10%, one’s 15%, you’ve respectively paid out three times on that order. Your margin goes out the door because you’re paying everybody, and you’re not paying for their contribution in closing that order, you’re paying them for the full order. Affiliates play a big part of that piece because you can’t send them a partial amount.

Can you estimate how much money you’re saving through tag management?

I would easily say more than a quarter million dollars in excess payouts. At my previous company we probably saved the company in excess of half a million to more than three-quarters of a million in the first year.

It ends up paying for itself, especially if you have a very robust affiliate program or you’re doing any type of CPA-based ad purchasing or CPA partnerships. You really only want to attribute and optimize based on their role, first in or last in. There’s a whole world of corrections and cancellations and fraud. If none of that existed, it probably wouldn’t be as good a deal. You have to have the ability to give that order a one-to-one relationship with a channel.

Interesting that you’ve been in the field of tag management for 10 years. How have things evolved?

Back in the day when affiliate programs were really starting to emerge and there were gobs of different networks out there you had a massive pool of CPA orders and more people doing CPA partnerships as more of an exploratory way to pre-test an agreement. One thing I noticed was that every time my confirmation page was loading I was using source code and broadcasting pixels to all my third parties. So I asked, “What do I need to do to clean this up?”

So the first incarnation of pixel wrapping was developed to say: if our system develops this source code as the final source code of record with this transaction, then it becomes associated with a pixel. That’s why it became called pixel wrapping. You associated whatever your onsite tracking mechanisms were to the different third-party pixels.

 Now there are new things bundled into tag management such as site speed, privacy, data collection. Do these features play an important role for Harry and David?

Site speed definitely is part of it. When I was doing the RFP for tag management one of the things I brought up was speed was not my main concern. There is a value to that, but it’s more of a side effect. Tag management has a lot more benefits than asynchronous loading. It’s going to save you money, give you a cleaner view of your business, give third party vendors and partners a clearer view of your business so they’ll be optimizing based more on real numbers.

Whereas if you have PPC advertising, there may be a lot of conversions, but those keywords might have been more of an influencer.

Speed is a benefit given the world we’re in, but I would never recommend somebody go to tag management simply to speed their site up another couple of seconds.

This is the first installment of a two-part interview. Come back next week for more!

A SEO brand search features in half of all top-converting user journeys

Attribution matters. Take search, for example. In e-commerce, SEO is the most powerful converter to a sale outside of direct-to-site navigation. Yet marketers direct the bulk of their search efforts – not to mention search spend – into PPC.

“Search is great, but you probably don’t understand what the real story is,” says Jon Baron, TagMan’s chief revenue officer and co-founder. “You’ve been overvaluing paid search but undervaluing the SEO element. It’s amazing how many marketers just don’t get that. SEO is more involved in conversions than PPC.”

Baron is discussing the results of an e-tail attribution case study conducted in April, 2011.

“Google PPC is good but it isn’t great. We looked at some clients’ data to see the real impact of search across all the channels, particularly SEO – the free stuff versus SEM – the paid stuff. SEO is a closer, particularly in brand search. Even in generic searches it seems to be performing a lot better than PPC.”

Is SEO a Quick Converter?

Is SEO a quick converter?

•As expected SEO brand search is a strong converter. Users search for brand terms when they’re close to making the purchase decision.

SEO generic search is the strongest non-brand campaign element as compared to display, re-targeting and email, with an 8.3% ratio of straight-to-conversion sales. This makes it easier to forecast sales for. It’s also less affected by changes to the media mix. Moreover, it’s a channel that drives direct ROI due to the self contained conversions.

Generic SEO Initiates Customer Journey

What happens when a generic SEO search initiates the customer journey?

From all journeys initiated by an SEO generic search, the majority of searchers convert via direct navigation or a SEO brand search.

SEO: Indicator or Converter?

Is SEO an indicator or a convertor?

• Analyzing the purchase funnel provides clear insight into the role SEO plays in the marketing mix.
• SEO generic search is an initiator. Over 91 percent of clicks are not last events.
• SEO generic search has over 3X the amount of first events as compared to an affiliate campaign.

You probably don’t want to abandon brand PPC entirely, but until you’re absolutely clear on attribution and the role SEO plays in conversions, you don’t want to mis-allocate the marketing budget. Only looking beyond last click reveals these hidden conversion paths, the simple fact is some channels are bound to look better than others with so simple as last-click attribution. While these results are for a single retailer in April 2011, the findings that organic search out-performs PPC has come up so often that we decided to cut our PPC spend and develop a content strategy.

By reading this post, you are kind of proving the point!

Bryan Eisenberg

Speaker, best-selling author, columnist, digital marketing pioneer and more, Bryan Eisenberg has become something of a legend as a digital marketing pioneer, web metrics guru, and all around advocate of digital marketing best practices.

He’s also is the newest member of TagMan’s advisory board (see seperate press release). We sat down with him to discuss why he feels the tag management issue is an important one now, and what role he’ll play in moving the company forward.

Q: Why focus on this company at this time?

Bryan Eisenberg: A couple of issues. There’s several things that TagMan does is that are at the forefront of what marketers are concerned about. One of them is attribution management and the other big one is that people keep hearing they have to add robustness to their websites. “It’s just one more tag, it’s just one more tag.” People are getting tagged out, and this is a company that’s found a solution to deal with that. Getting anything changed on a website is challenging today. To get testing done you have to add these functionalities. When you have something that can eliminate one more frustration from the battle that marketing has with IT, it’s a good thing.

 Q: You’re deeply involved in web metrics and you’re a founding member of the Web Analytics Association. Does that play a role in your association with TagMan?

Eisenberg: Oh, definitely. That’s where my first battles in dealing with any kind of JavaScript tags really came in. Of course, you’re also looking at all the social plug-ins today. Publishers are adding ad features. It’s all become one thing after another. And it’s all focused on getting the data. This can help you with attribution as well as the management of all those tags.

Q: Let’s talk about attribution and why it’s so important to accomplish that task.

Eisenberg: Most people haven’t been aware of the attribution issue until really recently when Google began really talking about it, saying they were going to have their search funnel and their multichannel funnel. So people started getting the idea that it might be important. I still see very few people actually using it.

I remember we really started understanding the link between search and keywords and attribution about eight years ago.  One of our clients had a very broad term that never, ever, ever converted. Ever. So he decided he was going to shut it off. The following two weeks, his sales were down 30-something percent. He realized that what had happened was earlier on people were starting to recognize his brand, then later on in the search funnel he was showing up again, and they had confidence he was showing up and knew what he was talking about.

There’s no way for him to easily credit that earlier. He didn’t have a solution.

Q: Between all the things a tag management system can do: attribution, website optimization, even do-not-track compliance, what do you feel is the most important or vital?

Eisenberg: I don’t think we can narrow it down to one. Tag acceleration makes it important. But really it’s pain points, and where the market is. The nice thing is it’s one solution that has multiple purposes. That’s very valuable, as opposed to buying three different solutions from three different companies for three different problems. I’m always a big fan of that.

 Q: How aware do you think the market is of tag management as a problem? Is the market ready for this solution, or is it a year too early?

Eisenberg: This is one place where I think the U.S. lags behind the rest of the world. In Europe there’s been a lot more discussion about tags and cookies, privacy laws in general. People here haven’t been made as aware of it, plus there’s a lot more people in this market. It’s not mainstream, but it certainly will become so. One thing I’ve definitely learned is the second Google starts focusing on something and rings the bell, the more people actually catch on to it. They just did multichannel funnels, I think that’s going to help educate marketers. They’ll learn very basic stuff and they’ll want more.

Q: Talk a little about how you hope to personally contribute to TagMan.

Eisenberg: One of my main goals is the same goal I’ve had since Day 1: helping marketers become more efficient at their marketing efforts. Part of that is through education. One of the first things I started discussing with TagMan was showing them interesting research studies we should be taking a look at. We need to learn what marketers are talking about and what they’re interested in, and if we have to bring them in via their own interests, we’ll do that. We’ve seen that in some of the research that’s been coming out the past couple of weeks, such as the one on social plug-ins and another on Internet retailers and page speed.

Q: Is there anything you’d like to add to what we’ve discussed?

Eisenberg: For the most part, lots of American companies have trouble accepting companies from abroad as leaders. Apart from a couple of Israeli companies, like ICQ, U.S. marketers have not been accepting of international companies. A lot of them are innovating far beyond what we’re doing here in the States. Some issues have occurred there before they occurred here, like page management issues. TagMan has a track record, they’ve worked with big companies in the U.K. This isn’t something you just piece together.

Hanna Kimuyu: Greenlight initially integrated TagMan data (client specific) to understand the relationship between paid and organic search, but have since expanded this into understanding the full user buying cycle. The data findings so far have confirmed our initial thoughts that the user doesn’t have a preference between paid or natural search when searching for products or services. In fact, the cross interaction between the two media, suggests that users are just focusing on their ‘search phrases’, and then picking the most relevant brand to buy with. Furthermore, as advertisers diversify their online strategies more, the conversation becomes bigger than just understanding the relationship between paid and organic search. Brands should be asking themselves ‘what is the relationship between all online channels’ ‘do I have the right media mix’ and ‘is my strategy cost effective’.

TM: How is Greenlight applying that insight to search strategies and tactics for its clients? Can you give any examples?

HK: Even though search marketing is over ten years old, most advertisers are still using the first or last-click model, meaning anything that happens in between is completely ignored. Having both full click and channel path data allows Greenlight to analysis the entire user search journey, from first click to conversion. Resulting in several things:

1. De-duplication of data, no more over paying affiliate commissions.
2. Introducing Attribution modelling, fairer way of awarding affiliate commissions and sales/revenue to contributing channels.
3. The importance of each channel, specifically the role each channel plays within the buying cycle.
4. Transparency of the full click/channel path, what are users doing, what search phrases are they using and what channels are they interacting with to find the most relevant product or service? Are there are patterns in how users search? Can we use this data to shape our online strategies?

Stage one is very much about discovery – understanding the data/making sense of it. It should be noted that this isn’t a quick process, and getting all the relevant people around the table to discuss and analysis the findings is critical. At this point it makes sense to apply a ‘version one attribution model’, which again will need to be discussed and evaluated before making any further changes. Although this may sound like a time and resource heavy exercise, it is beneficial. Our TagMan clients are seeing cost benefits in year one, and now have a transparent view of how their users interact between the channels before converting.

TM: Paid search listings are often accused of gaining disproportionate credit for sales thanks to the predominance of last-click models, and the channel’s intense measurability. What’s your view of that debate and is the TagMan data Greenlight sees providing any illumination?

HK: For a lot of advertisers paid search represents a larger proportion of their online advertising budget, suggesting almost a reliance on the channel. If this is the true, paid search represents a larger proportion of the sales because in most cases users will finish their search journey on a ‘branded click’ i.e. brand search term. Especially, if the advertiser is bidding on branded terms, then the last click model will of course favour paid search over the other channels. In this instance, this is very much down to the strategy in place and the fact the advertiser has chosen a last click model – hence why ‘paid search is often accused of gaining a disproportionate credit for sales’.

The TagMan data has been pivotal to highlighting the ‘real’ role brand and paid search (as a channel) plays in the entire user search journey. The trick is not to work to a last-click model continuously, but to start off with a last-click model as a benchmark before moving into attribution, so you can really appreciate what each channel brings to the overall picture. Having gone through the same exercise for a travel client, initially we discovered that, on the last-click model, paid search represented 29% of all sales (of which 22% were branded sales).

Having analyzed the full channel and click path (search only) data we then applied a fair attribution model, taking the decision to downgrade paid search branded sales. The outcome saw paid search still being the second biggest contributor, delivering 25% of all sales. Proving that paid search was working just as hard as the other channels, if not harder, to drive sales.

TM: How, specifically, are organic listings revealing themselves as drivers of customers through the purchase funnel?

HK: First and foremost we’re confidently tracking all organic listings. I have to point this out specifically because in most cases the traffic and sales resulting from organic listings are normally assumed from the ‘whatever is left’ bucket. To explain, most advertisers will tag their paid for online activity, that being paid search, display etc, therefore leaving a bucket of remaining traffic and sales. With TagMan, Greenlight has been able to identify Direct to Site (DTS) traffic, i.e. domain, bookmarking and organic traffic specifically. Allowing us to confidently understand what value organic traffic and optimisation brings to an overall search strategy.

There’s no one approach or outcome though, the value is completely is down to the intended strategy. Using the travel client mentioned above, their intention was to use organic search to pick up the long tail, e.g. ‘hotels in New York with a swimming pool, close to Central Park’. This search term might sound unreal, but when a user is close to converting or has a specific product in mind, the long tail proves quite useful.

Traditionally (and it’s still the case) paid search picks up on most of this traffic. Long tail search, although low in volume, is cheap and effective, normally resulting in a strong conversion rate. However, if you have the flexibility to create specific landing pages for these type of terms (to which the travel client mentioned did) then it also makes sense to drive your organic listing there as well. Especially if targeting some of the more competitive terms does not cost in. With this strategy in place the travel brand was able to see the value in building such landing pages, and the role organic search played to its overall strategy.

TM: What new insight have you been able to derive about the way in which different keyword groups drive people from research to conversion?

HK:
1. The less surprising lesson but most valuable is the fact that a buying cycle does in fact exist. Users will combine generics, e.g. hotels in London, with branded, e.g. Guoman hotels in London; with more product/service led searches e.g. conference hotels in London. There’s no bias towards paid or organic (natural) search. If the listing or advertisement is appealing and relevant, a user will click – it’s simple! It may sound strange to highlight this point, but advertisers still don’t appreciate the value in combining a range of research, consideration and branded terms when bidding via paid search or optimisation for organic search. Users have become more sophisticated when searching for a product or service, therefore if a brand wants to be considered, then they have to be present throughout the users search journey.

2. The biggest surprise has seen the average buying cycles almost doubling for both retail and travel. Typically an advertiser will set a cookie length of 30 days maximum to capture a user’s interaction before conversion. From recent analysis into both the retail and travel sectors, it has become apparent that user’s are taking longer to convert. Part of this can be explained in the click/channel path. Firstly, the number of channel interactions have grown; as well as the number of searches conducted. Secondly, the user is looking for a ‘bargain’ – even if they decide they want to buy from a particular brand, they will still search for discounts. Lastly, users are savvier at searching, although generics still rule in terms of the number of searches made per month (volume) – users are combining a range of keywords before converting.

TM: Can we offer any more insight into the debate around the way in which paid and natural search strategy can be better integrated to increase conversions and reduce cannibalization?

HK: Yes – position analysis as part of the attribution. One of the biggest debates in search is – what is the benefit of having both paid and organic search listings for the same search term? Although we’ve been able to prove cannibalisation when advertising on the same keyword for both paid and organic listings via an attribution model; this data doesn’t take into consideration the position of each listing. There are plenty of research studies that prove there is an uplift in click through rate if both paid and organic listings sit alongside each other. That said, what is the perfect position combination?

TM: As online retailers gain clearer sight of their customers’ entire paths to conversion, how do you see their approach to paid and natural search evolving?

HK: Revenue-driven strategies; as a result of having a clearer understanding of how and what to integrate, how do we develop a strategy that can almost predict a revenue outcome? Allowing advertisers to decide where and when to spend. Furthermore, search as a channel isn’t just about paid or organic search. Social media advertising channels such as Facebook’s Placement Programme, or Google’s Display Network (AdSense and Double Click collaboration) are also components of search. How is this changing the data and our view on how search is contributing to the wider picture?

Paul Cook, CEO, TagMan says:

• Companies will be forced to allow consumers to opt-out out at a ‘tag level’ in response to to new EU privacy legislation and others.
• Wider uptake of attribution reporting/understanding sees dollars move away from brand paid search terms towards organic search display retargeting/extension.
• Someone needs to ‘manage’ all these predictions on Adexchanger as the industry evolves: Agnostic, boutique agencies will win back direct-to-vendor dollars and handle more supplier review processes/paperwork/analysis etc.
• Terry Kawaja will release a Monopoly Board which pivots into a DSP  (that’s an injoke, if you are coming from a background not infused in this data-driven industry)

Go download all of adexchanger’s predictions from industry experts here: http://bit.ly/Adexchanger2010

WHAT ARE YOUR PREDICTIONS?  Post in the comments below.

New York, NY – Judged by senior industry peers from the likes of Omnicom, Rapp, Wieden+Kennedy , MediaVest, Online Publishers Association and Return Path; the award represents “the best existing, new or improved analytics and measurement platform innovation to provide metrics and insights for advertisers, publishers, and marketers”. TagMan’s attribution focused technology beat out entrants and finalists, to be judged the clear winner by informed US industry heavy-weights in this exciting sector.

The DPAC Awards honor overall excellence and breakthrough achievement in US digital publishing and advertising. The purpose of the DPAC Awards is to recognize the outstanding efforts being made in digital publishing and advertising.
The award was accepted by Chris Brinkworth, TagMan’s CMO, at the DPAC Gala in New York City on December 9, 2010.

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