Becky Broe the second of our 2014 graduates shares her first week experience....
We have just welcomed our 2014 graduates to Maxus and over the next few days they will be sharing their experiences during their first week at Maxus. First up is AV Account Executive, James Bottomley.............
Speaking at Adobe's London Digital Marketing Summit, Will Hayward, vice-president, advertising at BuzzFeed said native advertising was currently seen as an example of the "blurring" of editorial and commercial.
This sounds a lot like the old marketing tool, the advertorial. And if native advertising is to challenge the advertorial format, it needs to be seen as a grown-up part of the media mix.
Advertorial – a one-sided approach
From my perspective an advertorial is an agency and client’s last ditch attempt to make a low interest category or brand interesting.
The reality is that the well qualified editorial team are often too busy filing interesting content to worry about the brand pillar of a personal toiletry product or holiday destination to provide scintillating content that aligns the best interests of all parties. The task is inevitably farmed out to interns or freelance writers, often on short timelines. The publication in this instance holds all the cards and takes a commercial approach.
In essence it is a parasitic relationship where a lot of the power is held by one side of the arrangement.
But publishers and media owners are facing a changing consumer consumption model that demands content 24 hours a day (accelerated by mobile devices). Current staff structures can’t support that and just replicating the same content onto every media outlet will surely erode any business model in the long term. Until these stakeholders find a way to financially monetise their digital offering, this is not viable in the long-term.
Native advertising – equal inputs and outputs
In comparison, native advertising offers equal benefits to all parties. Content, stories, opinions and points of view are all written in the brand’s tone of voice. Plus, the product managers still get their brand endorsed by a credible media publisher.
Yes, it requires more work from all parties: the brand to understand they are aiming to create true ‘content’ not just a picture with a publications endorsement, and the publication to understand that it should be seen as a solution to a content problem they are experiencing not just fast buck onto their bottom line. But as this approach is more collaborative – it offers a symbiotic relationship as opposed to a parasitic one.
If native advertising is such a win-win it shouldn’t be a particularly hard sell. However, the same barriers that come up every time a new development in digital media takes place are alive here.
Firstly, what role does it play in the media mix?
Native Advertising is about leveraging the valued, trusted editorial of the publisher in a way that doesn’t distract from the users’ experience, but instead provides an engaging content experience. If we believe this, then planning native as a way of combating lowering response rates from direct response display formats surely is not the answer. As an industry we need to make sure that clients don’t see it in that way, but instead see it as another string to the bow of digital media and measure it accordingly.
Secondly, who creates it? By its nature, native advertising doesn’t adhere to set formats; there can be no IAB standard. This hugely increases the number of creative assets needed for a campaign. However, as with other developments in digital media, formats that sit outside of standard creative (e.g. mobile ads, search ads, social ads) tend not to have been picked up by the creative agencies. This has increased the responsibility for media owners and media agencies to work on brands’ creative, or opened the door to niche companies to take advantage.
However, the first steps needed to over-come these challenges must be taken by media agencies. We must educate our clients on the features and benefits of native, as well as identifying the publishers who’re building out creative service teams to help brands create content that fits the voice of the outlet – an area which advertorials don’t match up. Finally, and most importantly, unless agencies and clients are prepared to effective measure native campaigns, we’ll all miss an exciting opportunity to satisfy consumer’s desires for engaging branded content.
Unless you live in a cave you’ll probably have had the mandatory summer email for sweepstakes; be it on the Open, World Cup, or Cannes. But now some of the smartest minds in our industry are pitching man against machine to predict the winners of Innovation at Cannes 2014.
Decoded, a coding training academy, have developed an algorithm called ‘The Oracle’, which they claim can predict the outcome using ‘big data’. This will be pitched against stiff competition – the Leo Burnett team who claim that its Cannes Predictions reel has an 84% success rate in forecasting Lion winners over the last 26 years. Leo Burnett has only missed a Film Grand Prix twice, and one of those years was 1997, when none was awarded.
So, what are they predicting? Leo Burnett have picked the Samsung ‘Smart Bike’ which claims to be the world’s safest bike. This is based on last year’s judge’s focus on ideas which have real human impact; combined with monitoring online buzz, local insight, and gut instinct.
The Oracle has picked ‘Beats Music’, the music streaming service. This decision was made purely on the basis of last year's data, looking at which agencies, which regions, which cities, which holding companies, and which kinds of campaigns had the greatest success.
So who will predict correctly? You’ll have to tune in to the last day of the festival on June 21st to find out. Personally, I’d like to think The Oracle is most informed, since it is predicting a 77% chance that WPP will outperform Omnicom in Film Lions. Come on WPP!
Last week saw an intriguing announcement from Sky for a service called #WatchOnSky which is enabled through Twitter. It will appear across Sky’s Twitter feeds and allow people to see the epic 'Game of Thrones' the gripping 'Mad Men', through to sporting events and movies.
The mechanic itself is simple to operate with Sky providing tweets about shows to people and if it includes the ‘#WatchOnSky’, it can be expanded to reveal ‘Watch’ and ‘Record’ icons that link directly to Sky’s mobile TV service Sky Go to either watch it on the go or record it to your Sky+ box to watch when you get home.
Sky currently offer 54 channels through Sky Go and this service builds on the Sky Go and Sky+ apps. This is all very handy for the consumer and puts them in total control of when and where they watch TV as more and more people move towards time shifted viewing.
Looking at this from a planners perspective this seems like a very clever move and will allow Sky to tap into a rich stream of customer data irrespective of the device the content is being consumed on as people have to be logged in to get access the service. As Sky moves towards a majority of Sky+ boxes and therefore Adsmart enabled households any additional data that can be collected and collated will allow them to build a richer picture of the makeup of individual consumers. This in turn will allow Adsmart campaigns to be more targeted and accurate than the standard BARB audiences that TV campaigns are currently bought against.
It’s no full solution to evolving the standard buying audiences and I can hear the digital teams scoffing at the prehistoric levels of targeting but it’s a strong step in the right direction. Let’s just hope that the twitter activity doesn’t retweet any guilty pleasures we record for everyone to see!
Marketing Mix Models(MMM) have, in recent times, increasingly come under attack from various sources, who question whether or not flaws in the underlying methodology mean that far too much emphasis is placed on short term volume driving activities (such as price and promotion), at the expense of more longer term strategies such as advertising investment:
The problem however lies not in the underlying methodology behind MMM, but rather, in its application to understanding the impact of different marketing strategies on the consumer’s journey to purchase a product.
Let’s look at the typical purchase journey:
Quite clearly, the consumer’s journey is a complex one and often begins long before the actual intention to purchase, with a shortlist of possible brands being drawn up through a mix of past experiences, peer recommendation and general brand awareness brought about through marketing and product availability. This brand shortlist is then continually refined the closer the consumer gets to the point of purchase, again having being influenced by past experiences, peer recommendation and general marketing activity.
At the point of purchase, the decision to purchase is likely to be heavily influenced by pricing, point of sale marketing and the alternatives available, and less so heavily influenced, by marketing more highly geared to influence higher up the consumer funnel.
Exposure and interaction between media touch points is complex too, with many channels (such as digital and social) interacting with traditional channels to influence consumer response.
Couple this with the fact that no two consumers are ever the same, then it becomes clear that today’s marketers are, now more than ever, in need of a framework that can help them understand this complexity and subsequently develop the right strategy to grow their brand.
MMM is the ideal methodology to accomplish just this task, yet many marketing mix models
fail to truly recognise this complexity in their design, instead condensing the consumer journey merely to the point of purchase, examining just the direct link between various marketing factors and sales rather than examining the true impact across the consumer journey.
It is therefore little wonder that such models fail to give marketers the depth of insight they so desperately need, and indeed overvalue the more direct sale marketing activities at the expense of their more brand led counterparts.
So what’s the solution?
The advent of so called ‘big data’ has meant that the breadth and depth of data that can be gathered on consumers is on a scale never before seen. This, coupled with the application of more advanced modelling techniques than the familiar time series based approach, has meant that over simplification of models and subsequent insights no longer need be a problem for MMM. At Maxus we believe that there are three areas of improvement any practitioner can make to their models so that they deliver true insight to their clients:
1. Include more granular, better tracked data sources
Combining the already well-established tracked data sources of digital and social media with customer level sales data and new customer level ratings data for offline media, means that models can, like never before, be built at the consumer segment level.
Modelling at this level means that marketers will be able to glean insight into how different media strategies influence different consumer groups. Ultimately marrying the delivery of the results with the segmentation and media planning work that was done in advance of a campaign at the consumer segment level.
2. Include additional KPIs within the models
Since the 1990’s, much has been made in accountancy circles of the so called ‘Balanced Scorecard’ (Kaplan & Norton, Harvard Business School) approach to evaluating business performance. Such an approach advocates the use of a more ‘balanced’ set of KPIs including softer brand and internal measures, as well as the
usual financial measures as a means to evaluating business performance. Quite obviously, such a framework has a place in evaluating the consumer journey and as such can be applied to an MMM framework to encompass a whole range of consumer KPIs, such as brand awareness and customer satisfaction levels in addition to the usual sales KPIs common to most models.
Inclusion of such KPIs would mean that marketers could gain insight into the true role more brand led marketing is playing, rather than focusing purely on its role at the point of purchase, an area where it is likely to be significantly undervalued.
3. Make use of more exotic model frameworks to model results
The big problem with the standard statistical modelling approaches to MMM is that they are unable to cope with the inclusion of multiple KPIs, or indeed the interaction effects that are likely to exist between them and the individualvariables they contain. However, a number of other modelling frameworks, such as SEM (structural equation models) mean that more complicated model designs involving multiple, interrelated consumer KPIs and associated explanatory variables can be handled within a single framework. This in turn makes estimating the effect of different marketing activities on all elements of the consumer funnel relatively simple, so that marketers can at last understand the true role different media play in eliciting a consumer response.
It’s clear then that MMM isn’t necessarily a flawed concept when it comes to measuring the impact of marketing on the consumer. Rather, that it can, with a few tweaks to the underlying data, model design and application, become one of the most powerful tools marketers can call upon to help decide on the correct strategy in today’s consumer landscape.