Gain Theory has a global partnership in place with EffWorks an initiative led by the IPA that champions marketing effectiveness measurement, culture & best practice.

Client side brands involved include Diageo, Jaguar Land Rover, Telfonica, Mondelez, Lego, Kraft Heinz, Unilever, Samsung + many more; alongside industry associations such as 4A’s, IAB and CAA ; and media giants such as Google and facebook.

As an unbiased direct-to-client consultancy that champions marketing effectiveness, Gain Theory’s involvement with EffWorks is to drive high value content and conversations that shape thinking around client challenges, measurement strategies and actionable insights that have a positive impact on the bottom line.

In line with this, Gain Theory has led the creation of a green paper entitled Marketing Measurement in the Digital Era. The paper was created in collaboration with Facebook, Google, Thinkbox, Royal Mail, Mondelez and folded in interviews with Dixons, Samsung, Direct Line and many more client side brands.

The green paper intends to provoke debate and act as the foundation to further research and best practice in 2018.

Key themes:

  • Marketing – definitions
  • Effectiveness
  • Metrics that Matter
  • Measurement Strategies: what good looks like
  • The Future
  • 6 Step Marketing Effectiveness Plan

REGISTER FOR PREMIUM CONTENT AND UPDATES

Register to automatically receive the latest industry news, thoughts and trends, and gain access to premium content.
Or to login.

WORK WITH US

Find out how we can help, demo our products and get more information about our global cross-sector experience.
CONTACT

JOIN US

If you think you have what it takes to make a difference at Gain Theory, please check out our careers page.
CAREERS

Despite all the hype, for MTA to be useful its limitations must be clear and clearly communicated.

For many, Multi-Touch Attribution is both exciting and intimidating. The ability to track a sale back to the marketing initiatives that produced it has rightfully garnered a lot of fevered interest. If executed properly, MTA can enable prescriptive and granular media optimizations in near real-time that create significant ROI improvements.

The phrase is thrown about emphatically with terms like Big Data, User Level Analytics, and Real-Time Learnings. All that hype can create confusion, and ultimately, an expectation that can’t be met. Precious little airtime is given to the nuances and pitfalls of implementing MTA. That’s not to say it shouldn’t be activated, but that for it to be its most useful, the limitations and nuances of MTA must be clear and clearly communicated.

Understanding the desktop/mobile divide.
Industry reports and surveys suggest the average US consumer uses 2.3 internet-enabled devices. But MTA datasets usually show fewer than 1.6 devices per user. That’s a significant gap, and savvy clients will be expecting 2.3 because they’ve seen the industry reports and think their cross-device ID is weak.

To be sure, cross-service solutions are not perfect. They are a rapidly-improving component of the ad tech landscape. But in reality, the bigger culprit is that your desktop and mobile ad placements may not be as tightly aligned as you think. They target two similar (based on demographics and psychographics) yet different sets of consumers.

A simple way to dissect this is to create two user groups—Multi-Device users and Single Device users—then profile the media activity of these groups against each other. This will reveal sites that over index for Multi-Device users. These sites may represent a small percentage of the media budget that is causing the gap.

Integrating offline media is not as simple as advertised.
All MTA sales pitch decks have a slide about the integration of offline media, with a chart showing significant web traffic spikes attributed to TV’s impact. This approach is quite often naïve and breaks down in a few ways.

For brands with massive website traffic, TV airtimes do not consistently create obvious web traffic spikes; without the obvious traffic spikes TV’s impact can’t be seen. In addition, TV cannot drive immediate in-store purchases the same way it drives immediate .com visits. This is critically important for brands less concerned with online metrics and more concerned with in-store sales.

And the approach does not easily scale to other offline channels beyond TV. The other offline channels are not designed to elicit immediate response. As a result, alternative approaches for integrating offline media are often required.

Deploying MTA results via a true DSP integration is easier said than done.
Your DSP has a highly tuned and specific algorithm that adjusts bids on an ongoing basis. While MTA providers will trumpet “Partner Integrations” and delivering MTA results directly to DSPs, it is an entirely different challenge for that DSP to then incorporate those MTA results into the bidding process. If not engaged early in the process, DSPs may crudely apply up-weighting or down-weighting bids based on features of the Attribution analysis, which may not really result in optimal bids.

In general, as analytical outputs become increasingly granular, it is becoming more of challenge for downstream partners to implement them. Any ad tech partner that you’d expect to leverage the MTA outputs may require a change to their scope of work in order to undertake it.

Offline purchases may require special considerations.
E-commerce revenue, digital media ad spend and the overall percent of transactions completed via credit card are all going up over time. These shifts are major components of what makes user level MTA possible as they all generate user level data. But what about cash purchases? These are inherently anonymous and, for some verticals like QSRs, may represent 50 percent of sales. Cash purchasers may have far different media consumption habits than credit card purchasers. Tuning media via MTA outputs could be inadvertently tuning your marketing efforts towards credit card purchasers and away from cash purchasers, which could create longer term issues.

Every aspiring brand will be forced to encounter at least a couple of these issues as they tackle MTA. If you’re not prepared for them, your MTA implementation could stall and ultimately lose traction. Your best bet for success is to go in with your eyes wide open and expect that your MTA provider fully understand your business, how you sell your product and to whom and how you plan and execute your media and marketing activities.

Russell Nuzzo is Global Head of Attribution and Marketing Technologies at Gain Theory.

Market Mix Models, where one focuses on a single KPI like sales volume, are an extremely powerful technique and especially useful at disentangling the key elements of all the marketing levers that are available – price, promotion, advertising and so on.  Add in some enhanced granularity – modelling CPG by SKU and retail account, for example – and the technique becomes even more powerful.

But even the best models report back that an impact on your single KPI could not be found for some parts of the marketing mix.

This is not because these initiatives don’t have any impact.  It is more to do with the naïve measurement approach that is adopted by some marketing mix professionals.

Now, I’ve long been a believer that any marketing activity should ultimately be assessed on its ability to drive sales and profitability.  Else, what’s the point in it?  But the way it does this and the time period over which it works does not have to be as simple as “engage customer base with social media in week 1 and see sales go up in week 2”.

We’ve had the path to purchase  more than a century.  Let’s be smarter about using it.

In the modern era of digital media, instant response and online purchases, we are the first to admit that the path to purchase is changing.  But it is still key in building our understanding of how brands interact with the ecosystem which they inhabit.  Marketers use path to purchase to plan their campaigns. Modelers, who are  responsible for assessing the effectiveness of campaigns, should start using it too.

And when we talk about the path to purchase , we’re not talking about simple linear stages  that a customer goes through; becoming aware, interested, then desiring your brand and finally taking action and purchasing.  We doubt this was ever really the case.  It is hard to see how it’s the case now.  Stages are blurred and marketing can affect none, one or even all of the stages.  What’s more important is that some marketing channels won’t have a direct effect on sales at all, but will help to build the effectiveness of other levers.

Our solution is Integrated Marketing Response. There is no preconceived shape to the path to purchase  – it is an atheoretical approach that allows the data to tell her own story.  And instead of focusing on a single KPI like sales, it examines as many KPIs as required to derive a holistic understanding of the marketing ecosystem.

The strength of this approach is that you  no longer need to make excuses as far as measurement is concerned – blaming the inability to measure something on esoteric technical or data concerns.  There may not have been a direct effect on the end goal from some marketing stimuli, but then it probably wasn’t designed with this in mind.  Does anyone seriously believe that a company that succeeds in boosting its re-tweets by 10% will see a corresponding increase in sales at the till?  Well, perhaps –  if it is communicating a huge  discount. But we don’t need to rehash arguments about what short termism  will do to your brand health and profitability.

imr-diagram

Instead it is quite likely that these tweets will feed into some intermediate stage that may in turn feed into sales.  Let’s look at a simple example:

Diagram 1 shows a stylized example of an IMR ecosystem.  Caveat that while Gain Theory’s experience suggests that there are similarities across brands, each IMR is bespoke to a particular client and brand.  We can see from the schematic that some marketing initiatives have a direct effect on the end KPI (increased sales) while others are purely enablers, working with other stimuli to make them more effective.

To summarize, if you run an MMM analysis, the marketing ROIs will be based completely on the direct effect.  If you run an IMR the marketing ROIs will be based on both the direct and indirect effects.  This holistic view of marketing performance will lead to greater understanding of the impact of all touchpoints, as well as enhanced efficiencies within budget setting and allocation.

This approach is not theoretical: it is a proven success across retail, CPG, pharma and tech brands.

The WPP Global Retail Forum is a continuing education opportunity designed for marketers in retail. This year’s event featured the likes of Samsung, Dell, and IBM to name a few, speaking about key shifts in consumer buying behavior and ways to better connect with today’s shopper.

Jennifer Hahs – Research Director at Gain Theory – took the ground to download the biggest takeaways to help keep marketers one step ahead, to become faster and smarter in the ever-changing retail landscape.

We have curated this interactive, all device friendly playbook, so you can take away the major themes:

1. Get Back to Basics
Optimizing existing practice.

2. Be Nimble
Changing things that aren’t working.

3. Be Disruptive
Reinventing the norm.

4. Be Kind
Connecting with humans.

5. Future Now
Embracing the next generation.

6. Engaging Today’s Shopper
Seeing through the customer’s eyes.

To see the full download, click on the animated gif below and follow the arrows.

WPP Global Retail Forum: The Gain Theory Download  

 

The raison d’etre for the majority of Market Mix Modelling agencies is to calculate the marketing return on investment, or MROI.  Gain Theory takes a different approach – knowing the ROI is nice, but does little to solve the pain points of our customers –how to optimize marketing investment, the allocation between media channels and to ensure that all touchpoints are working coherently.

As one Marketing VP recently said in an independent CMO survey: “MMMs provide some insight into making better investments, but that is still fairly one dimensional”.

Because we start from a different position – dynamic improvement rather than static reporting – our approach is also different.

The common approach to media impact

By far and away, the most common approach to estimating the impact of media is to use an ad stock.  This may largely be seen as taking the ratings that your target audience had an opportunity to see and then decaying them.  Using a decay allows the media to be tested for an immediate effect, as well as an impact over the medium and longer term.

Now, this approach is fine if you are only concerned with identifying the ROI.

But it says nothing about wastage and it gives little insight into weekly phasing or even where diminishing returns begin to set in.  This is because a rating has little definitive to say about the chances of your target audience hearing or seeing an ad.

Ratings are a trading currency.  Nothing more.

Consider a simple example.  What do 20 TV ratings actually represent from a viewing perspective?  It could mean that 20% of your target audience have had an opportunity to see (OTS) one exposure.  Or it could mean that 10% are at 2 OTS.  Or some other combination.  On its own, it is impossible to say.  As ad stocks are based on this rather ambiguous metric, they have little to say about the level of reach or frequency required to drive improvements in your ROI.

Our tried and tested AdModel approach is much more forward thinking and considers five key parameters that provide key information for all stakeholders.

  1. Effective Frequency    
    How many exposures need to be seen to trigger a response?
  2. Recency Frequency    
    How many exposures need to be close to the purchase?
  3. Recency Window    
    What do we mean by ‘close’ – a week? 2 months?
  4. Memory Decay    
    How long is the exposure remembered?
  5. Habit       
    Is there repeat purchase?

The fifth parameter – Habit – describes the long term impact of converting new users – basically a measure of trial and repeat.  They may be completely new to the brand, or they may be existing users for who marketing has helped them discover new opportunities for use.

Going beyond ROI to help marketers take action

Identifying the first four parameters defines the budget required, the phasing strategy, and optimal investment.  For example, knowing that for your brand consumers need to see 4 exposures, 2 of them in the last 7 days throws up a completely different approach than if consumers just need 2 exposures, just 1 of which can be seen anytime within 2 weeks of the purchase decision.

Planning on norms, benchmarks and experience can lead to some serious inefficiencies.  Let’s look at the following simple example.

base plan to optimised plan

ratings alternative plan

The base plan from the agency seemed OK – continuity was deemed important, and running with a broadly constant level of weight.  However, the AdModel tells us that, to trigger a response from those active in the market, we need:

admodel table

Using this insight we can deliver a 30% increase in the ROI.  Based on science, not hunch.

As you can see, some big improvements in efficiency, just by understanding how media is working for you.  And this is for just one channel – the same efficiencies can be seen across the media and marketing mix.

This approach has been tested across all verticals and across all continents.  If you want to move away from reporting just an ROI to dynamically improving your marketing investments, it’s time to rethink your approach.

With so many different marketing channels out there today, it’s difficult to identify what drives sales.

In this paper, we present a new solution to an age-old problem – how to effectively measure the long-term effects of advertising.

Some people view this as being impossible, others do it inaccurately but we’ve figured out how to get it right. Here we discuss the issues involved, dismantle existing systems and present our own solution.

Inside this paper we cover:

  • Why is this important to me?
  • We need a floating base
  • What are the existing measurement methods and why don’t they work over long periods?
  • What attempts have been made to tackle this?
  • What is the solution?

To download the article, click the link on the right.

 

 

Digital marketing channels today are divergent – search, video, social, display, email, mobile – the list goes on. Marketers have a myriad of options to choose from to reach consumers to hit KPIs. But the biggest challenge is understanding which digital media work best…and how to optimize those.

The holy grail of many brands today is establishing which digital investment gets the credit for delivering a conversion event. Where should we spend our money? What can we cut from the budget? How? When?

As more media is bought digitally, more data is produced and with that comes an ability to measure effectiveness at a granular level.

The future is increasingly connected and for some big digital advertisers, requires the right measurement solution.

Digital Attribution can provide the right measurement and optimization solution. But you need the right tools and conditions to do so and what’s more – it’s not for everyone.

We have compiled an 8 Step Guide to Digital Attribution to help navigate marketers through the subject and understand whether it’s a journey they want to embark on.

The 8 steps are:

  1. Significant Digital Media Spend
  2. A Clear Online KPI
  3. A Skilled Team of Data Scientists
  4. The Right Purpose
  5. The Ability to Optimize Quickly
  6. The Right Data Set-Up
  7. Unified Digital Tracking
  8. The Right Methodology

You can read the in depth article published in AdMap, by downloading the article on the top right hand corner of this page.

Or

Visit our digital-attribution.com website to view the video.

 

Matthew Chappell, Partner at Gain Theory, attended the IAB Video Conference: Thinking Differently in London on Wednesday 16th November 2016. Here are his thoughts from the event:

Halfway through AOL’s session, Mark Milling asked the audience to put up their hands if they’d seen the new John Lewis advert. And then hold them up if they’d seen it online first. And then keep them held up if they’d seen it on TV at any point in the last week.

The only people who didn’t have their hands up to start with were probably asleep following lunch. Almost all of those who had seen it had seen it online first. Only seven people in an audience of 600 had seen it on TV at all. Seven.

Online video is no longer the future – it’s here. But how do we make the most of it? And, as the question posed by the conference title asked, how do we think differently?

First, a look back. In the early noughties, when digital was emerging, brands talked about how much money to invest in digital. Then, they talked about how much to invest in specific channels. Now, with the biggest digital channels we need to be asking how we allocate spend within them and how we create content that fits – what is the right message at the right time to the right people?

This is especially pertinent in video. In the past, brands put their TV ad online and that was that. Now the opportunities are limitless. Indeed, according to Millward Brown the average consumer spends 65mins a day watching video on mobile or tablet (vs 61mins on TV). There is vast potential attention but brands need to capture it quickly.

Two of the best sessions, from Facebook and Google DoubleClick, focused right in on this.

The Google DoubleClick session, run by Atossa Vaziri, discussed three different types of video content: meal, snack, bite. Sometimes you want a three course meal, or a three minute brand video; sometimes you want a snack. Sometimes you don’t even have time for a snack, just a bite of your friend’s cake. At different times you have different needs, and video advertising can and must reflect this. For example, on Facebook mobile, 98% of videos are watched in portrait (according to Jonathon Milne, CrO Celtra), most with the sound off. Advertising in this circumstance should probably be bite or snack sized, not a four course French dinner.

Ian Crocombe, from Facebook, also discussed three different ways of telling stories and capturing attention. He started with the old fashioned TV ad: a 30s build to a climax, with the brand displayed at the end. In the online video world this is flipped on its head, you show the brand and the punchline first, before exploring further in the next however many seconds. There is a third way, by which a brand pulses impact, humour, and emotion throughout the video, such as in the McDonalds example from Brazil, below. This is a fascinating way to grab attention and hold it for a long period, in this case 1min 45s.


Both told the same story in slightly different ways, but the takeout is the same. As demonstrated by Lucy McHenry from Twitter, Nielsen have shown that there is little correlation between video length and engagement. However, 81% of videos which drove high engagement had a hook in the first three seconds. And most good videos were optimised for sound off.

The main goal for advertising is still to capture attention and engage with consumers. There are many ways to do this, and for some brands this might not be video. The great thing about any digital media is its agility – the ability to test and learn quickly, fail fast and move on.

What we learnt today is that more brands than ever are willing to do this; to think differently on how to use video to improve their marketing effectiveness.

 

How can a brand maintain or increase sales during a recession?  For many marketers, pricing becomes one of the focal points of a brand’s marketing strategy in a downturn: many companies will decrease base price levels in an attempt to hit ambitious volume targets set during happier times. 

However in the recent recession, rising production costs have affected many consumers in the opposite way: they are being faced with increasing prices in-store even as producer’s profit margins have been squeezed.  This is backed up by this week’s release of inflation figures showing a rise in the Consumer Prices Index (CPI) to 2.7%[1] partly driven by increases in food and confectionary prices.

What, then, should a firm do to optimise their pricing strategy?  Raise price or lower it? Hold steady or follow the competition?  Getting the base-line pricing right can make or break a brand’s bottom line during an economic downturn as shown in research by KPMG which suggested that “business leaders estimate more effective pricing could increase their firm’s profit margins by 11% on average in current market conditions”.  One of the best ways to work out what to do is to model the impact of pricing decisions on volume sales.  We typically talk about this impact in terms of an “elasticity”: where the elasticity is high, responses to price changes are large; where the elasticity is low, responses to price changes are small. 

In a recent white paper , we’ve explored some of the benefits of using a price elasticity approach to the marketer – including calculating what the optimal price should be and running scenarios based on how your competition might respond.  We’ve also looked at the potential pit-falls and curious results that emerge from such analysis – including a recent case of a positive price-elasticity found in an econometric study.

No model can ever forecast perfectly the changes in volume associated with future price adjustments: but by understanding how past movements have affected previous sales levels (including the relative impact of changes vs. own and competitor lines) the marketer can make better plans for hitting next year’s targets and optimising future revenue.

[1] http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/october-2012/index.html

I was watching The X Factor with my Dad the other weekend: “The adverts,” he said, “are the best thing about this show. I don’t know why we don’t Skyplus it and just watch the breaks.” Guffawed, we did, at this. Dad, you’re so funny, we chuckled, you should be on Gogglebox. Then he woke up from his traditional pre-Christmas slumber, and stopped dreaming this sorry scene.

But his dreamlike state has a point. Last week was a huge week for TV adverts. More than ever, TV programmes are just the content behind ad delivery. Don’t believe me? Then why was ITVBe invented? With more than 13m YouTube views last Christmas, the John Lewis ad was more popular than the most-watched Christmas Day programmes1.

TV advertising continues to be a “big thing”. It continues to be invested in, at growing levels. It feels like new media channels are emerging every other day but TV holds its place in most big brands’ plans. Whilst other ‘traditional’ media channels decline, TV grows. This can’t just be media buyers holding onto their old ways, can it?2

In the digital age, TV does two jobs really well: Direct Response driver or Brand Builder. It is this duality of purpose, alongside the huge reach and viewer experience available, which keeps TV in its place at the top.

Direct Response Driver

The internet has changed the type of brands who advertise on TV. For example, it is impossible to watch a sporting event without bumping into a plethora of gambling firms. Partly due to a change in regulation, but mostly because of the ability to immediately impact acquisitions, their spend has increased from £84.9m in 2008 to £141.5m in 20133.

Any brand with a strong online presence is on TV, and on it loads. Brian, from Confused.com, tells you how easy it is to compare car insurance, now, on your mobile. Trivago helps you plan your trip there and then by using their app. WaterAid shows you how easy it is to text to donate money to their cause.

Confused.com advert

With this rise in internet response being driven by TV, it becomes important for measurement to keep up and assess that link between the online and offline worlds. Any solid ROI or media mix analysis will look at the impact of all media on all parts of the business, whether this be through econometrics, agent based simulation, or A/B testing.

Brand Builder

If potential customers continue to talk about your ad and share it on YouTube, you’ve got organic and viral growth on top of your paid activity. This isn’t particularly new. People have always talked about good advertising, but the talk is happening more quickly – Twitter is the new watercooler –  and it is measurable. Our previous pieces on Social TV and Long Term effects of Advertising have covered this in a lot of detail.  There is a clear link between TV activity and brand building.

Sainsbury’s Christmas advert

Whether or not you like the new Sainsbury’s TV ad, it has had a clear impact on social media, with #Sainsburys rising to the top of the trend charts within hours of being aired. What is important for measurement is to know what it is you’re trying to measure: is it tweets, Facebook likes, awareness, consideration, web visits, app downloads, or sales? Once the KPI and a solid brief are defined, measurement becomes a lot more straightforward and robust.

Conclusion

Robust measurement of TV, of its impact on response and on conversations, underpins it’s continued use. Measurement and analytics inform brands, media agencies, buyers, and many more, on TV’s place in any media budget (in terms of spend and timing), on how TV interacts with digital (with Search, Twitter, Facebook, YouTube, Display, Emails, etc.) and finally how all these media channels should be part of an integrated plan.

© Gain Theory 2017. All rights reserved.