What is a Brand Painting?

One of the key lessons that any analyst needs to learn is the ability to turn numbers into insight which can be “read” by almost any client. While analysts deal in numbers all day long, many of the audience for their research see numbers as an impediment to their understanding of a subject. Therefore every analyst needs a good set of charts, visualisations and other associated images to help them tell the story of their analysis to a wider audience.

For Marketing Mix Analysis (an analytical technique which seeks to estimate the incremental impact of each core marketing activity on total sales performance), one such key chart is the “Brand Painting”. A Brand Painting is a visual decomposition of the sales performance over time showing how much each driver is contributing at each point in time.

Here’s an example of a brand painting taken directly from our modelQED™ application:

In this picture, we can see a “base” level of activity which contains a range of inputs including seasonality, longer term market trends, special events and in the case of output from modelQED™, the impact of competitor marketing*.

We can then see the incremental impacts of TV, Press, Radio and Outdoor advertising as well as some short term promotions plus the detrimental impact of price rises on total sales.

What makes this a useful graphic? Well I think the following:

• The Brand Painting gives you a great view of sales performance across time – something often ignored
• Brand Paintings are a great way of assessing the overall impacts of drivers – whilst the ROI on an online campaign may look fantastic, has it actually moved the needle? Being able to see the relative sales increase from each channel is important
• Trends can become more obvious – the impact of all those small price rises can soon add up to a lot of units for an elastic brand but an elasticity value of -3.2 often fails to convey the magnitude of this change
• They can give a great insight into the medium term impact of marketing – the period over which the short term impact decays

Any pitfalls?

• Brand Paintings don’t show the ROI of investments – a large impact may or may not have a large investment behind it
• You can’t easily get any sense of whether there are diminishing returns present in the drivers
• You can only plot Brand Paintings if a model uses an additive mathematical structure – or at least if only makes sense to in these circumstances

So the upshot is this: I love Brand Paintings and almost every client I’ve ever worked for instinctively found them valuable when I presented my analytical results. If you don’t have the right applications then they can take a little bit of effort to construct in Excel or SAS but ultimately they’re worth it.

*note that modelQED™ does estimate the impact of competitor marketing but it is not charted on Brand Paintings by default.

Microsoft patents obvious idea

US patents are a strange thing. We recently consulted a patent attorney about our software product modelQED to try and determine what protection if any we could obtain for some of the more unique parts of the software. The answer we got back was not the one we were looking for. We were told that there was no chance of patenting a clever mathematical idea or software process here in the UK or the rest of Europe. However we were informed that about $30k would suffice should we wish to write (and most likely obtain) a patent in the US at very low risk.

It appears that the standards are very different on both sides of the Atlantic – so much so that even Congress is now looking at reforming the system to stop “obvious” inventions being patented.

Microsoft are sure to have an entire raft of patent and they’ve added another one into the mix in the last few days (see http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220070174117%22.PGNR.&OS=DN/20070174117&RS=DN/20070174117). This application is for an ad targeting system making use of “biometric sensors, cameras, remote controls, or other accessories” to monitor who is watching a TV or other device and adjust the content accordingly. This is akin to web surfing on a PC who knows exactly who is using it at all times.

As I’ve mentioned in the past (http://marketing-works.blogspot.com/2007/06/privacy-concerns-to-hamper-measurement.html) privacy concerns will undoubtedly throw a spanner in the works should Microsoft try to come up with a system such as this. In many ways this device would be some sort of Direct Marketing nirvana if there was a return channel to allow purchase. Obviously there is if the device is online and this is the market that Microsoft, Google and even some ad agencies are going after. However I would bet that these patents will come to little in the next five years or so. Privacy issues are becoming more and more important and “big giant head” devices that communicate with big brother aren’t exactly popular. Even if they can somehow find a way to use ad dollars to subsidise such a device, will people really embrace a new advertising channel such as “sniff you first” TV?

Update on modelQED

Just a quick update to let you know how modelQED has been received in the marketplace.

We're really excited by the reaction we've had to the modelQED application that we just released onto the market (click here for details). When we demo the product, people instinctively "get" it and that's a great feeling. Two comments particular stand out for me:

1) "It's a Ronseal job" - this comment was made by the head of a major UK consultancy who understood that we're not trying to reinvent the wheel by making an uber-complex analytical tool. We're pragmatists and we try to be honest in our conversations with clients. Hopefully this is paying off. (FYI - Ronseal is a UK brand of consumer decorating materials famed for it's advertising tag line of "It does exactly what it says on the tin)

2) "It's amazingly beautiful" - a verbatim comment (honestly) from the head of a US agency who felt that our product was both easy to use and intuitive. This felt great because we've really tried to make our product easy to understand for an analyst. Try using standard SAS or SPSS charts to present information and you'll understand why we spent lot's of effort on "look & feel". It's not that they can't make great charts that tell a story but it takes a lot of effort.

We've still got things to improve and we're not being complacent. However it's our baby and we're proud. If you haven't seen the product and want a trial, go to our website and request one. No obligations. That way you can judge the above comments for yourself!

modelQED Launched - finally!

Today we finally launched modelQED™, a marketing mix analysis tool (econometrics if you prefer) which will hopefully help to democrotise the usage of this powerful analytical technique.

For many years, i've figured that marketing mix analysis was actually a fairly well understood tool by many advertisers. There are many articles saying that it needs to be performed by professionals with years of experience. However my personal experience was that for 90% of the models i've ever created, the simple straightforward model was often the best. My econometrics knowledge was only used on the most specialist assignments. For the rest of the time, i was following a well defined process which in most cases gave the correct answers. modelQED™ is designed to deal with these challenges in record quick time and leave the hard core analysts to tackle the remaining challenges.

As with all things marketingQED are trying to do, we've focused our efforts on making modelQED™ both simple to use but also powerful in context. By this I mean that the users interaction with the package is made as easy as possible whilst the analysis delivered is exactly what would be required for the majority of mix modelling. The feedback to date is that we've largely achieved this. I think we will continue to develop the product focusing on even more simplification and user friendliness.

modelQED™ solves lots of issues for modellers but this is only the beginning. Give me a call or drop me an e-mail if you want a demo of this truly unique tool.

We have many other products in the pipeline. Hopefully the market will find these tools useful.

Any comments on the screenshots etc - please post or e-mail. Feedback always appreciated.

"You can't trust early adopters"

So says James McQuivey from Forrester who was commenting on the slow (read no) growth in iTunes video downloads as reported here - http://www.theregister.co.uk/2007/05/14/forrester_online_video/.

Early adopters have apparently skewed the forecasts for PAID online video downloads. Many analysts assumed that once the rest of us "got" it, we'd behave in the same manner as the early adopters did. However we didn't and it’s now looking like iTunes isn’t going to be the killer investment Apple and their media owner backers had hoped for.

What does this mean from marketing analysts? How does it make a difference to how we think about marketing? Well it shouldn’t change backward looking analysis too much in practice. However the focus has to shift for many organisations to start answering questions like “how do we shift this in the future?” It really brings home a point which was made to me over and over again by former colleagues – namely you have to add judgement to historical analysis in order to create a more reliable model for forecasting. In the past, I’ve been involved in a number of workshops which seek to qualify historical models with beliefs about how the future may differ from the past – Delphi style has been common. These workshops are a great way to test new hypotheses about the future and one key topic must encompass the question of “how might our consumers differ in the future?”

As many of you will be aware, my company is about to launch modelQED – a backward looking modelling tool which creates marketing mix models in record time. One of the key benefits of this tool is that it will cut down on the amount of time spend on backward looking analysis enabling organisations to spend much more time looking forward and understanding how the future will differ from the past. For me this is a winning combination – reduce historical analysis time (and increase the quality of the analysis) + systematically review how the future will differ from the past.

I hope that this powerful combination will prove irresistible to many organisations!