Tag Archives: Awards

Peter O’Neill has Received a DAA Awards for Excellence Nomination

The founder of L3 Analytics, Peter O’Neill, has received a DAA Awards for Excellence nomination.

Peter O'Neill L3 Analytics

The DAA Awards for Excellence, which are run by the Digital Analytics Association (DAA), aim to recognise the world’s most influential digital analytics practitioners.

Peter O’Neill has been shortlisted in the Most Influential Individual Industry Contributor category for creating MeasureCamp and MeasureBowling, and sits alongside Nicolas Malo, fellow Co-Founder of MeasureBowling. Peter’s nomination which was submitted anonymously reads:

This guy did what no one did. Take care of Europe and the rest of the world (except USA). He brought Analytics to our door through the creation of MeasureCamp and then, in combination with Nicolas Malo, through MeasureBowling. These guys changed the professional life of thousands of people with FREE events. They just ROCK.

MeasureCamp is a free-to-attend unconference, different to any other web analytics conference held around the world. The schedule is created on the day and speakers are fellow attendees. Everyone is encouraged to discuss and participate in sessions, even to lead sessions themselves. The whole point is that attendees focus on what they find most interesting and useful. There have now been 13 MeasureCamps across six cities with at least four more MeasureCamp cities joining this year.

The DAA, which announced the shortlist on the 19th of January 2016, is now calling on all members to place their votes for the person who has had the biggest impact on the analytics community. The first stage of voting is open until the 1st February 2016 and votes can be placed via the DAA website. Finalists will then be announced on the 8th February 2016 and the winners will be decided by an esteemed panel of judges, with the results being announced at the Awards for Excellence Gala in San Francisco on the 4th April 2016.

Peter O’Neill comments, “I am humbled to have a received a nomination for the DAA Awards for Excellence and would like to thank the person who put me forward. My passion for digital analytics started about a decade ago and my focus over the past few years has been on finding new ways to bring the analytics community together to share knowledge.  This has led to the creation of events including MeasureCamp and MeasureBowling. I would like to extend my congratulations to all other shortlisted nominees, it shows the exciting growth in our industry with so many people doing great work.”

To find out more about the DAA Awards for Excellence and to view the full shortlist, please visit the Digital Analytics Association website.

Three reasons for measuring multichannel marketing campaigns

My original blog post on measuring multichannel marketing campaigns was focused on optimising future marketing performance across all marketing channels for an organisation and I made recommendations on what I believe are the best ways of achieving this goal.  However I didn’t mention or discuss other reasons for wanting to be able to allocate revenue generated (or alternative goals achieved) between different marketing channels.  While the aim of the organisation should be maximising value across all marketing channels, for practical business purposes, there are other reasons for wanting to be able to measure or calculate that revenue split.

As I see it, the three key reasons for wanting to be able to attribute revenue to the different marketing channels (and broken down further within channels as required) are:

  • Optimise future marketing spend
  • Calculate payment for past marketing activity
  • Internal business performance reporting

Optimise future marketing spend

As detailed in the previous post, I recommend:

  • Evaluate the campaign based on the business bottom line (e.g. revenue for ecommerce sites) rather than trying to calculate revenue generated by channel
  • Evaluate each channel based on success actions that are relevant to that channel
  • Ideally all evaluations should be made by comparing actual performance against a forecast
  • Use results from testing and previous campaigns to guide and improve future marketing performance

Calculate payment for past marketing activity

One of the factors that prompted me to write on this topic originally was the focus by so many companies, both client side and agency side, on campaign attribution just so that each channel could claim the appropriate amount of credit.  This allows the internal staff or the external agency in control of that channel to receive an appropriate level of compensation for their work.  But as I have said, I don’t think calculating revenue generated by a marketing channel/campaign is possible to do accurately.

In good news though, I don’t think that should matter when it comes to calculating the payment for that marketing channel/campaign.  Value is something defined by the two parties so what matters is that an agreed methodology/formula is used.  For example, for a paid search campaign being run for a client by a search marketing agency, the agreement could be made around one or more of the following areas:

  • A set fee
  • A proportion of total spend
  • An hourly rate for managing the paid search campaign
  • A set fee per search engine click
  • A set fee per visit as measured by web analytics tool of choice
  • A set fee per visit in which predefined actions occurred as measured using the web analytics tool of choice
  • A proportion of revenue generated through visits that originate with a paid search click as measured by the web analytics or campaign measurement tool of choice using a last touch campaign attribution method
  • A proportion of revenue generated through visits that originate with a paid search click as measured by the web analytics or campaign measurement tool of choice using a first touch campaign attribution method

As long as both parties are happy that the payment method chosen reflects the value provided by the search marketing agency, then there shouldn’t be any problems.  The client will need to ensure that the method does relate to the impact of the marketing on their business.  And the agency will need to ensure that the method sufficiently rewards them for time and effort.  For both parties, it would be ideal that the better the agency performs in creating value for the client (as opposed to just working more hours), the higher their reward.

Internal business performance reporting

I am quite aware of this requirement due to the time I have spent creating dashboards for weekly performance reporting for clients.  Most top line summaries within my dashboards will include some data on the performance by traffic source (including non marketing traffic sources such as direct).  While these might not be the Action Dashboards that Avinash recommends, I still believe this information is useful for understanding performance – with a view to using this understanding to take actions.

And if you are going to include a single metric per traffic source, the best metric of course would be revenue (or equivalent goal for a non-ecommerce site).  So how do I recommend doing this if I believe you can’t accurately attribute revenue to traffic sources?

I would still go ahead and report this performance in terms of revenue or equivalent end goal using an attribution method of choice, which for me would ideally be last touch.   The reported number is not the revenue generated by the traffic source but if last touch attribution is used, the data will show the revenue generated during visits that originated with click from that traffic source e.g. a click on a sponsored listing.  As with most web analytics analysis, the focus here should not be on the absolute numbers but the trend over time, highlighting sudden spikes or falls and/or the general direction for each traffic source.  This information is relevant and actionable.


It would be great if we could accurately measure or calculate the revenue generated by each marketing channel and element within a marketing channel.  Life would be a lot simpler and indeed a happier place.  But it’s not possible and life is not simple.  So what’s the next best option?  To just use what data you can get anyway acknowledging that it will be somewhat inaccurate?

I say no on the grounds that the inaccuracy will be of a sufficient level to lead to poor strategic decisions.  Instead I have recommended different approaches to be used for the three key reasons for which it would be incredibly valuable to be able to match a revenue number against a marketing channel.

What do you think?  Do you agree with me?  Feel free to leave comments here or, if you are going to be at JUMP, look me up there and I will be happy to have a chat in person.

Winner of the Econsultancy JUMP blogging contest

It was a bit of a shock and a great surprise to see this tweet pop up on my screen last Fri afternoon

I had written this post on measuring multichannel campaigns the previous week upon my return from travels and was only able to submit it due to the deadline being extended by a week.  Given that JUMP is a conference all about joining up online and offline marketing to achieve better results and that it targets marketers, it was a surprise to win by writing about the measurement of marketing performance.  Particularly since a key argument of mine, that campaign attribution does not and can not work, is counter to what most people in web analytics are saying, working on and selling.

I intend to expand upon some of the points I raised within the post in the future, ideally with examples and case studies.  But in the meantime, let me just say thank you to Econsultancy for selecting me as the winner of this competition and for the prizes, particularly the pass to JUMP.  This should be a great conference based on the line up of speakers and topics, am looking forward to hearing and discussing some interesting ideas.

Let me know if you are also attending and want to catch up for a chat while there.

Measuring Multichannel Marketing Campaigns

With the incentive of an iPad, eConsultancy membership and a free pass to JUMP, I spent a proportion of my time while hiking around Peru trying to develop my thoughts on optimising the return from doing both online and offline marketing.  Naturally, as a web analyst, my focus on this is related to measuring and understanding the performance of marketing campaigns – based on the idea that the more that you understand about the performance of past campaigns, the more you can improve your future campaigns.

The approach that I am developing towards evaluating marketing performance can be used across both online and offline marketing.  It is intended to be used to optimise the financial return that is gained from investing in marketing via multiple channels , taking into account the performance of individual channels and their combined impact on business performance.

The future is campaign attribution??

Working with online businesses, the common approach is to use campaign attribution to allocate revenue to the different marketing channels that are being used. (I am going to keep it simple here by only referring to ecommerce websites that have revenue as their goal although the same principles can be applied to non-ecommerce websites using alternative conversion actions).  Whichever campaign attribute technique is used (first touch, last touch, weighted attribution, etc), it provides a revenue figure that each marketing channel can claim credit for earning.  With this data, the business owner or marketer can calculate the ROI against marketing spend by channel and to understand what the impact would be if marketing spend for a particular channel was increased or cut.

There are known issues right now with this approach due to limitations in the various models.  However web analytics and other marketing management tools are developing more sophisticated techniques for attributing revenue to the different touch points.

This is naturally incredibly valuable information as long it reflects reality and I just don’t think it does. It can only be based on known online touch points prior to a purchase being made online and this leaves out so many factors:

  • Offline marketing influences are not captured as these cannot be tracked online (except in the use of vanity URLs or similarly identifying features)
  • Non marketing influences such as a friend’s recommendation or product reviews are not captured
  • Only online touch points on the same computer used to make the purchase are captured, when people could easily have researched the purchase on a different computer
  • Purchases made offline are not captured but these could also have been impacted by online marketing and should also be used in any ROI calculations

Beyond all this, marketing campaign attribution relies on being able to convert a person’s buying decision into simple numbers, to calculate the weighting each touch point had on that decision.  I don’t believe this is actually possible as people would not be able to accurately say themselves what motivated them to make a purchase – did you book that holiday 15% due to an email, 25% due to a link on an affiliate marketing site and 60% due to a paid search link?  This is further complicated by the interaction between different information sources and the requirement to develop a model that works with all people (maybe some people are impacted by the first touch point and others by the last touch point).

What are business owners and marketers really trying to achieve?

My philosophy about all this is still in development (and I totally reserve the right to change my mind based on feedback from others) but my current recommendation is to lose the belief that you can accurately or usefully attribute revenue between different marketing channels.  Instead I think you should evaluate the performance of marketing at two levels:

  • Overall business performance
  • Individual marketing channels based on success actions

The real question that business owners and marketers need the answer to is what to do for the next campaign, not how much revenue did each marketing channel make in the last campaign.  While that information would be great to have in order to plan future campaigns, I don’t believe it is possible to calculate.  Instead the focus should be on gathering useful information that is accurate and that will allow for the optimisation of future marketing campaigns.

Evaluate overall business performance

As a web analyst, I could list off several pages of potential metrics for understanding performance across different marketing sources and several might even be valid KPIs.  But at the end of the day, only one number is going to matter and that is profit.

The measure of success of a marketing campaign is quite simply whether the incremental profit generated was greater than the incremental marketing spend (including salary costs for people working on the campaigns) during the defined time period.  A simple way of looking at things maybe but it is what the CEO is going to do.

This simplistic approach to evaluating the performance of marketing covers both online and offline marketing and also purchases made through websites or in store.  As the public is using multiple channels to research your products and then makes the purchase via whichever method is most convenient (or offers best value), this approach covers all angles and most importantly covers all customer behaviour.

Note that it does rely on a decent forecast being made of what revenue would be if nothing changed, whether this means no marketing at all or no extra investment in additional marketing channels.

This approach may also just be the best way of evaluating how different combinations of marketing channels perform.  While there are numerous statistical and econometrical approaches that can be used, the business bottom line is the one true test.  Different combinations of marketing investment across multiple marketing channels can be compared between regions or different date ranges in order to determine the optimal combination.

Evaluate individual marketing channels based on success actions

Being unable to attribute revenue to marketing channels does not mean that their performance should not be measured or evaluated as successful or not.  But instead of linking performance purely to purchases and thus revenue/profit, each channel should be evaluated based on predefined success actions.  These are specific to each marketing channel based on what you are trying to achieve with the investment in that channel.  This applies to both online and offline marketing channels.

The success actions can be linked to website behaviour, other online behaviour or any offline behaviour.  Examples of potential success actions include:

  • Website visits from a particular traffic source
  • Website entries on a particular landing page
  • A level of engagement with the website (e.g. view at least two product pages) for traffic from a particular traffic source
  • In store voucher redemptions
  • Use of a particular hashtag on twitter
  • Increased brand awareness as measured by a survey
  • Increased sales of a particular product, either online or in store
  • Increased sales within a particular store

These success actions need to be defined in advance as part of the marketing planning process, both what the actions are and at what level can the performance of that marketing channel be considered a success given the investment in it.  It is this information that is used to review the performance by marketing channel and to decide on future investment in it.

Learn from experience

So if you want to achieve excellence in using multiple marketing channels, my advice is to measure performance, compare against forecasts and use what you have learnt to improve future marketing campaigns.

Do not try and split your revenue between marketing channels, it is just not possible to do accurately. Instead evaluate individual marketing channels against success actions relevant to what you are trying to achieve with that marketing channel.

Be prepared to experiment with different channels, all the old ones and the new ones.  But look to the bottom line to understand which combinations work best.  Use the data gained from previous marketing campaigns to improve and optimise your future marketing campaigns.

This post is part of the #JUMPchallenge, a blogging competition designed to raise awareness of how to join up online and offline marketing, launched to support Econsultancy’s JUMP event.

This post was first published on AussieWebAnalyst on 17th Sept ’10.