Thanks to Marin Software, Criteo, MediaMath and eXelate for being part of the video.

For a recap on many of the tags that are running easily through TagMan, visit this post “what tags & pixels does TagMan work with?”

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.

They are looking for data to prove to the business that the $2,000 they spend each month on PPC, for example, is delivering value so that next month they can spend $5,000, next quarter $25,000, and next year $100,000 across an array of channels.

This also points us to the idea that marketers new to digital are starting from the point of view of really understanding what combination of online activity drives sales, rather than individual channels. Those of us that have been in the digital sector for a long time have to unlearn the old way of thinking and the incumbent ecosystem has to adjust too. For the new age of digital marketing is one where marketers appreciate that customers don’t work in channels and neither should we.

It’s also nice to know TagMan’s appeal isn’t just for large brands with money to devote to doing what they do smarter but also smaller companies who want to be smarter from the get-go.

As marketers run more and more advertising channels in driving users to the website, they’ve rightly relied on tracking to identify what worked and what didn’t. The problem is they have been looking at the wrong thing and basing media decisions from the wrong perspective.

The last-click model has been the demise of many marketing channels which perhaps played a valuable part in the brand discovery or product selection process of the consumer. Once the consumer has decided what they wanted to buy, they’d typically go directly to the site (via a branded search term) and convert in that visit. As the last click, that branded search term would have been credited with the sale and all the valuable media they consumed in getting to that decision was ignored and not credited. This leads to money being directed away from valuable media and fed into the direct channels and very much away from profitability.

With our clients now basing media decisions on attributed data (where the credit of the sale is shared between all campaigns in the path to conversion), very different media decisions are being made and happily they are reporting a great increase in overall performance of their activity. Check out our new Boden attribution case study to see this in action.

Why it’s taken so long for the industry to grasp this with both hands I don’t know, but now the tide has changed this is excellent for marketers for a number of reasons:It makes marketing much more fun as you can try out lots of smaller channels using attributed data to show their true value

1. It makes the Web better as publishers can be more focused on providing the excellent content to capture the user’s interest rather than keep trying to get them to click through to an advertiser and buy right away
2. It will continue the growth in the digital marketing industry as ROI get higher and higher (perhaps to the detriment of the other traditional media)
3. Oh, and it will get you a promotion and that healthy bonus as you will see far greater returns for your marketing than before!

“TagMan has achieved significant traction amongst web marketers by taking away the pain associated with deploying tracking pixels, speeding up their pages and providing multichannel attribution reports in real-time,” says company CEO and founder Paul Cook. “We are very pleased to have an exceptional team of deeply experienced advisors to help up take TagMan’s sophisticated proposition to mainstream marketers.”

The Board includes:

Brendan Condon: With 25 years of global media experience across several TIME WARNER divisions (serving the past seven years at AOL overseeing its global Mobile, SEM, Affiliate and APAC advertising businesses and before that, 18 years at TIME Inc), Mr. Condon specializes in media monetization, especially digital with and local cross-media advertising.

Formerly, the Managing Director of AOL’s Platform-A International advertising division, based in London, Mr. Condon led the business with full P+L responsibilities, and a team of more than 500 employees across 10 European countries and Japan.

Calvin Lui: The former President & CEO of Tumri, the leading provider of dynamic creative solutions for online display advertising, Calvin Lui has a strong history of building teams and scaling businesses, both online and offline, with particular emphasis on sales, marketing, business development and corporate development. Prior to Tumri, Mr. Lui served as COO of Connexus a leading Internet performance marketing company, and also served as President of its Traffic Marketplace division.  He has also worked as SVP of Sales and Marketing at Ticketmaster, served as CEO at TheMan.com and held management positions at Lycos, St. Paul Venture Capital and Credit Suisse First Boston.

John Marshall: has 30 years experience of entrepreneurship in the software and Internet industries. He is a Netscape alumnus and went on to found ClickTracks , a pioneering web analytics tool.  Mr. Marshall invented and patented several important innovations within analytics, including the now ubiquitous overlay view. ClickTracks was acquired by Lyris Technologies in 2006.  Mr. Marshall is a founder of Market Motive, providing training courses and certification in online marketing.

Tom Sipple: is currently a Vice President at Interactive Corporation (IAC), leading the monetization strategy, direct sales, aggregator partners, mobile and advertising operations groups for Dictionary.com (part of the family of brands). He joined IAC from Yahoo! where he spent eight years in various roles, but most recently as Managing Director of Yahoo, SE Asia managing Yahoo’s user and revenue growth in the emerging markets of Vietnam, Thailand, Singapore, Philippines, Indonesia and Malaysia.  Prior to moving to Asia, Mr. Sipple was a Strategic Account Director in display media sales for Yahoo based in San Francisco. He also worked at USA Today leading circulation and advertising for the travel category.

TagMan (www.TagMan.com) is the single-tag solution to the problems of online campaign tracking and slow pages loads due to excess tags. By acting as a single, universal tag and interface through which tracking tags and pixels can be deployed to a retailer, e commerce or advertiser’s web site, online marketers can save time and money in the way they track campaigns and see how all online channels are working together. Clients include Virgin Atlantic, Subaru, Boden, Laura Ashley, Thomas Cook and Air New Zealand. TagMan was founded in November 2007 and has offices in New York and London.

The digital currency of awarding credit is still on the last click that generated the sale, and this is what they use for awarding their affiliates and other CPA channels commission for the business they generate. However, they use the attribution analysis of the campaigns to work out if a CPA channel is producing a positive ROI – and therefore if they should continue to invest in it.

Non-brand SEO vs. Affiliates

I’d like to illustrate this by looking at two of the campaigns we are tracking for them: non branded SEO and the affiliate sales through a well known and respected network.

On a last-click win analysis (how commission is awarded), non-brand terms in natural search results generated 600 conversions with revenue of £18,000 and the affiliate generated 4,300 conversions with revenue of £170,000.

On the face of it, it doesn’t look like SEO non brand really does much for them, and that the affiliate is doing a far better job.

The catch comes when marketers have a hunch that due to cash-back and voucher-code sites, the affiliate is cannibalising the sales of the other campaigns – shall we call it goal-hanging – and make a decision to stop working with the affiliate on this hunch.

Applied attribution

However, if you look at the sales and revenue each campaign generated not by last click, but by an attribution model it tells a very different story and with the data you can make a much better decision.

Using a flat attribution model where the credit and revenue of each sale is split evenly between all the campaigns that show up in the path to conversion, we see that, over the same date range, the non-brand SEO attributed sales (that is the sales where non-brand natural results show in the conversion path) were 4,050 with revenue of £145,000 and the affiliate generated 1,900 attributed sales with £73,000 revenue.

This shows the marketers hunch was partly right, but the key number is the attributed revenue by both campaigns.  For ease of numbers, let’s say this client had a profit margin of 10%.  Therefore the profit on the SEO work was £14,500 while the profit of the affiliate was £7,300.

Change in budget spend

As it happened, this client didn’t spent nearly £14,500 on SEO marketing and as a result of this data now spend incredibly more and are looking forward to seeing this channel push up last click conversions to other channels.

Moreover, while the affiliate wasn’t generating as much value as reported by last click, the profit was still higher than the commission paid out – i.e. the affiliate is still a channel with positive ROI even with the cash-back and voucher-code sites, and so the client also continues to invest heavily in this area.

I purposefully haven’t provided the length of time this analysis was over as the idea can work for smaller companies just as much for larger companies.  Whether this data spans a single day or three months, it still ensures that as a marketer, you are basing decisions on data and not hunches.

This post will identify the differences and why any marketer would actually need both an analytics solution and TagMan.

TagMan is an independent container tag solution.  Typically, it sits on every page within your website and will manage the serving of all your tags including campaign tags such as affiliate or PPC or email conversion tags; web analytics tags; multivariate testing tags from technologies like Optimost and retargeting tags from services like Criteo.

Via a user interface, you, the marketer can load up any of these tags passing any page parameters (such as basket values, departure dates, product IDs etc.) into the tags without needing the resource of your time-poor IT colleagues.

As part of the way TagMan works, it can track every event a user clicks or views including SEO and report that full path to conversion.  This is where I think the misconception of an overlap comes in.

The overlap misconception

The difference is that with web analytics, you retrospectively analyse the data to improve future media planning – possibly looking to attribute the credit of sales against the many campaigns a user has responded to.

With TagMan, while you still retrospectively analyse the data, you also set up an attribution model to run in real time.  On that cherished confirmation page, all the campaign tags are served conditionally through TagMan, and so depending on the campaigns the customer has responded to and the attribution model, TagMan will only serve the campaign tags which have led to the sale.

To make this seamlessly work with your CPA partners (such as performance marketing agencies or affiliate networks), TagMan goes a step further by intelligently serving the portion of campaign tags related to the portion of credit the campaign will get for each sale.

Example

By way of illustration, imagine a user clicks on a PPC link on Monday, clicks on an affiliate link on Tuesday, and clicks on an SEO link on Friday making a purchase of £90.  If you are running a flat attribution model – where the credit of the sale is split evenly by all the campaigns which drove the sale; on the confirmation page, TagMan will serve tags for all 3 campaigns, and in the case of the affiliate tag, pass a shopping cart value of 1/3 of the sale (ie £30).

In this instance, the affiliate is then able to claim their full commission on the revenue they collect through their tags and no negotiation is required after the event.

Without the tags being conditionally served, these campaign tags will be served for every sale, and the network will then claim for every sale which was generated by a click on their marketing.

Trying to develop a multiple awarding mechanism through web analytics would take analysis of each sale to calculate the correct portion of credit for each campaign, and then to present the findings to each network and partner to work out the commission payments.  All in all a fairly time consuming and messy way to work!

Now while they happily suggest consumers go elsewhere to pick which TV they want and visit their website to make the sale, many brands should be asking for consumers to consider and select products from within their own site as they will have a much higher chance of eventually selling that product to the prospect when the time comes.

With this in mind, using the traditional mechanism of a ‘last click’ wins model, only the marketing efforts which drive the visit of the eventual sale will get the credit, whereas Dixons rightly highlights the prospect’s need to spend time considering what to buy before the final plunge.

By using a last click win model, all the visits to your website which are for selecting and considering products will get no credit for the sale, even though they have an immense effect on the eventual conversion on that customer.

By running an attribution model which shares the credit of a campaign against all marketing events the prospect has responded to, your media planning will be more wisely spent, and the eventual returns much higher.  Ie, users who have visited the site already and looked for products are far more likely to buy that product from you on an eventual ‘purchase’ visit.

A few case studies to prove this are on the way from a number of major high street retailer and travel companies.  Get in touch and I’ll make sure you see them first!

While retail clients consistently favour paying on a last-click wins basis – ‘the last argument before purchase must be the most convincing’ – there are many examples of how marketers are more sensitive to their users’ psychology.

Examples of ‘engagement’

Here’s a few examples of where engagement mapping across the standard digital touch points – display (banners on publisher sites, ad networks), affiliates, email marketing, paid & natural search -has been relevant:

1.I went to a presentation a few years ago by a rich media vendor where a study showed the optimum number of times a banner should be seen (to maximise click-to-conversion rate) is three.

2.Another study showed that video ads should be between 10-20 seconds in length to optimise click-through rate.

3.A marketing manager at a mobile phone reseller spent greater budget on display than the click-conversions warranted – he could see data that showed users were more likely to convert if they’d seen banner ads, even though the last touch point before conversion was consistently clicks via PPC or SEO.

4.A gambling client of mine would pay the CPA bounty on a first-click wins basis; they were certain that getting a user to visit their site in the first instance was the hardest part of the sales process given the saturated market (their target market was users who were already a member of 3-5 gambling sites).

So some verticals rely on exploiting their users’ impulse to purchase with timed-limited offers specific to them while others feel they’re racing to reach their target market, and use engaging (sometimes uncomfortably distracting) copy to stand out; interrupting a user’s typical ‘ad blind’ journey.Others contrive for the user to encounter and compare their product in search cycles and user reviews; convinced theirs will win through on merit.

My point is that marketers are responding to their users’ psychology with competitors, buying cycles and the holistic digital journey in mind.It’s apparent that the brain reacts to repetition, unusual stimuli, and that our thought processes before ad engagement can positively or negatively affect that engagement (what was the user doing before we dragged them to our site?).

We are thinking in engagement maps, touch points and ad sequencing; and it’s clear this is having an impact on purchase probability.We’re moving away from dividing budget by sales channel and to spending on the combination and timing of digital media.

So why one commission?

But, why do we still tend to pay 100% of CPA bounty to the significant channel (whether first or last click, for example), instead of paying a significant percentage of CPA bounty to the significant channel?I don’t believe first or last click is how we should attribute credit, pay our acquisition bounties or plan our budgets.Many sales channels are adept at prolific cookie dropping, so that they exist in the majority of conversion paths.Others will even persuade users to delete their cookies so that a specific newly dropped cookie overrides them.

So what I’d recommend is a ‘best click’ model. This is how that might be achieved:

1.Use a first or last-click model as a foundation and rank your engagement points: highest for those you feel are doing the most selling (e.g. affiliates on a one-day click window, perhaps banners on a one-hour click window); lowest for those you feel are the most transactional (i.e. those that are the obvious route to buying a product – and retailer – a customer has already decided on) or are serial cookie droppers (e.g. PPC on brand terms, maybe one-day view windows on reach ad networks).

2.Arrange for the correct conversion tag to be written into the conversion page based on rank and timing, using them to award higher proportions of commission (and overall credit) to those high-rank channels where they appear in the conversion path.

Dynamic awarding & attribution: proportionate commissions

Dynamic awarding & attribution: PPC given higher priority

Our charts show how – by giving one channel a higher priority (because you rank it as being a better driver of ‘unique’ sales) – you can also give it a higher proportion of credit and commission. In the second chart, PPC is ranked as highest priority so – even when it appears as the second to last click – it gets the most credit.

This is a complex process but one that requires a useful exercise – to really think through which channels you believe in as drivers of sales you wouldn’t otherwise have, rather than those that deliver customers who were already committed to you and your product. Once in place, the way you rank channels and executions (like keywords) and attribute commission can be constantly refined.

Of course, even this model is flawed; any model that tries to pinpoint the significant engagement event among many is inconsistent with our users’ psychologies and prone to abuse. Still, attributing credit across multiple touch points, from both a reporting and awarding point of view helps to alleviate the distortion created by the sales channels currently fighting for that first or last click.

Progressive attribution

CPA sales channels should be incentivised for finding the right users and speaking to their psychology, and discouraged from just putting themselves at the right point of the conversion path to claim the final click. We can now pass a weighted proportion of the CPA bounty to an affiliate, or that can load a conversion tag for a weighted proportion of the time; all according to the attribution model selected.You may know this method as dynamic awarding or applied attribution.

Despite the flaws in drawing accurate conclusions from user journeys, I feel the marketing community intuitively builds a critical mass of engagement.I’ve lost count of the marketers I know that can’t prove why display contributes to post-view conversions, but are convinced it does (there’s a fair few that can prove it too!).Ad saturation here or under-exposure there can reverse the build-up of pressure – the critical sales point must be capitalised on before the pressure fades or is directed away by a competitor.Modelling this critical mass of engagement with correct statistical treatment (which is what the digital marketplace is acclaimed for), will obviously yield dividends.

It’s launched a campaign to build a team of people to investigate marketing attribution so that all channels in the online conversion process (including natural search!) get fair credit for the work they do in delivering a customer, even if they’re not ‘the last click’.

Shop.org is inviting people to volunteer their help and says it will, and I quote:

”

• Review current multi-channel allocation methodologies for determining incremental sales, highlighting the pros and cons of various approaches
• Review available and emerging technologies for tracking and allocation
• Recommend best practices for retailers to implement in their organizations to effectively measure the incremental impact of their marketing dollars”