Attribution.    Real-time,  Applied Marketing Attribution.

Short version of this post: You are not handling Attribution in real-time.  You may ‘think’ you are – but you are not.   Attribution models, tell you what to do – but you still need to do it. TagMan can help you.

Long version of this post

Stuck in the lounge at the airport with 2 hour delay is a perfect chance to ask write and ask YOU, the reader,  to question the difference between ‘Attribution Modeling and Attribution Reporting’  (ie Passive vs Real-time).   Please, do comment below with your thoughts.

First, some words.  What is Multi Touch Attribution, Multi Channel Attribution, Marketing Attribution, Media Attribution (take a breath) Credit Attribution, Affiliate Attribution, Search Attribution…   There is just so much buzz, so many articles, so many conferences, reports etc but lets be clear  - there are only three groups of people reading this.

• a) You are a company talking about doing it (eg – what should be done, what should you do and which channel, advert, partner specific campaign attribution should go to)
• b) You are a company doing it right now. ( ‘Real Time Attribution or ‘Applied Attribution’ – making it happen, right now.)
• c) You are a competitor(ish) reading our blog posts

Which are you?   Talking (Passive) or doing (Applying)?

Hate to tell you (& you can tell the boss) – you are all most likely still in Group A   even though you thought otherwise.    You are talking, not doing.

Humor me…

Even if you have a great SaaS ‘Attribution Management’ vendor with charts that tell you great things.  Even if you have advanced advertising analytics tag(s) that you have installed (at great labor) extensively on all of your pages – you are still looking at ‘what you should have done’ and ‘what should be done’.    It’s all still passive –  It’s not Real-Time reporting.

Those 200 different charts and models in that ‘platform’ who’s tags you have coded on all your pages (how long will you keep those attribution tags there btw?)  – they are not helping you in Real-Time.   That attribution provider that shows you all types of models and reports from the past year about various shares of  profit, revenue, conversions etc…    it’s still not happened.   It is still just ‘passive models’.  Sure – you know something about what is going on, but you are still looking at ‘what you should have done’.  You need to ‘apply’ it now.   Not wait 3 months.

If, like me, you work better on analogies.   Let us look at it this way:

Picture yourself on a plane (unlike me, I’m stuck in the lounge still). You are currently passive.

You open up the inflight magazine and look at the map in the back of where that plane can fly in America and in the world.   You know, that pretty, impressive map that shows every possible route across America. It’s just screaming out colors and ‘impressive routes’.    (cant wait to see that on an ipad)

It would have taken many aviation experts  months to chart those courses (and in many pretty colors, lines and graphics) and many graphic designers worked on making it look nice – but you and all your fellow passengers like me are still not actually at the destination yet.    You are still passive on the Tarmac (most likely O’hare) waiting to take off from point a (where you are sitting passive) to get to b (your destination (applied)).     No matter how many times you look at that map or how many models of that journey (200 different routes in 200 different colors) you look at – you still need to ‘Apply in Real-Time’ a journey.  The journey has not yet happened. You (or the pilot) still need to chose a route, with all the differing variables and make it happen.      You need to ‘Dynamically Apply’ in ‘Real-Time’ the idea of getting from ‘a’ (where you are) to ‘b’ (where you want to be).

Group a (talking about doing it) (looking at and drawing lots of routes in pretty colors but still on tarmac)

Group b (Doing it right now) (making that journey right now, in Real-Time) (EG, Dynamically Loading Tags and Reporting)

Having one, agnostic tag management solution – that connects all data, connects all partners and ‘serves all tags’ changes your multi-touch attribution results dramatically.    The process of “Applied Attribution in Real-Time” assists your business get a competitive edge.    Where many vendors simply provide a company with ‘visual attribution modeling’, because TagMan controls ‘what tags get served, when, why and to who’, it allows advertisers to ‘APPLY Attribution in Real-Time. This means you are saving marketing spend now – not 3 months later.    (You get  to where you want to be now and not sit on the Tarmac for 3 months).        If you were to put that into a monetary perspective and you could make real-time savings and get access to an extra 15% of your budget now to spend elsewhere… not in 3 months time – you can see the competitive advantage.   Our clients can (and do).

Ask your current multi-touch attribution or attribution model provider or even your current lite-tag container provider if they can do this.   They may tell you that you can take your key models and ask your media teams to ‘apply them’, but that defeats the purpose – how long will it take to apply that model?

By managing ‘all tracking tags and vendors’ through one vendor agnostic platform, TagMan offer the built in ‘off the shelf’ ability to enable real time, dynamic attribution awarding and reporting across all marketing service providers including Natural Search and Direct to Site. We allow you to create custom real-time models to instantly remove payments claimed by partners, when you know the catalogue number should get that credit, not an affiliate.    You want to de duplicate that affiliate TODAY, now, in real-time, using complex rules based on cookie window, model etc.    We help to ensure that only the conversion pixel for the MOST RELEVANT partner gets loaded up.  We ensure that you only report on what matters and only pay on what matters .  Your internal reports match your vendor reports and gives you an instant ROI ‘now’, so you have that money to spend elsewhere ‘now’ to grow your business and sales – not in 3 months time when you may get round to it when you’ve finished drawing different pretty routes.

We would love you to ‘apply’ in ‘real-time’ for a demo of TagMan. Drop us an email to find out more.  We are all happy to show you a quick demo and show you case-studies of where clients are saving money and truly on top of Applied Multi-Touch Attribution.

NEW YORK (July 21, 2010) TagMan, the marketing tag management system that solves the problems associated with site tagging and tracking of online marketing campaigns through a single universal tag, today announced a Board of Advisors tasked to consult with the rapidly growing company on its strategy and tactics.

“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.

Chatting with a TagMan client (who I can’t name) about the attribution data we provide them, I was really impressed with the approach they have taken in assessing the quality (and ROI) of campaigns and how they use this data in their media planning.

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.

Many companies have commented that through their use of an advanced web analytics company like AT Internet, Omniture or RedEye they already have analysis of every campaign a user clicks on in their path to conversion, and as a result they struggle to see how TagMan can help them beyond that.

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!

I’d like to thank Dixons for their latest tube ads which should bring to light how important the consideration and selection of products are as well as the final purchase in the sales process.

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!

Paul Cook, TagMan CEO, has written a detailed blog post on marketing attribution on Econsultancy, explaining exactly how advertisers can attribute proportionate amounts of both credit and commissions to different marketing ‘events’ based on the role they played in delivering a website customer.

In the post he says: “First, it is important to make the distinction between attributing credit to channels in your reports for better planning and dynamically awarding proportions of commission to partners using an attribution model.

“Obviously, Google isn’t about to accept a lower percentage of the CPC because you tell it the click it delivered only played a small part in a sale. But you can attribute different levels of ‘credit’ to it in order to provide you with data that may help determine your future spending plans.

“However, for CPA channels, where the advertiser controls the commission that gets paid, clients really can begin to award percentages of commission to multiple channels, based on insight into the role they played.”

He then explains precisely how attribution works and what it means. Whether using attribution models to attribute ‘credit’ to channels more fairly or to actually reward commission-based channels, it’s the start of a new phase, where the industry can finally move away from ‘last-click wins’.

We know that consumers will engage with a brand several times before purchasing and we’re moving to a point where this journey can be accurately mapped and assumptions made.

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.

Great to see that Shop.org, a collective for online retailers, is putting real effort into getting heads around the problem of marketing attribution.

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”

TagMan CEO Paul Cook has contributed a key blog post to Econsultancy.com revealing how the way Google Analytics tracks natural search makes effective marketing attribution a rather challenging business for site owners.

Full post here: http://econsultancy.com/blog/3963-does-google-analytics-overstate-the-value-of-search