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Archive for the ‘Measurement’ Category

  • Mar
  • 20

Pinterest’s New Analytics Tools – the Why and the How

In a likely step on the road to monetisation, Pinterest announced the launch of a suite of analytics tools last week.

The tools will be available for free to any user that has gone through the automated verification process on its website.  Stats available include the number of pinners and pins collecting material from the brand’s sites and the number of repins (and repinners) those initial pins received. Brands are also able to see their total impressions and overall reach on the network, as well as referral traffic, in terms of clicks and unique visitors, that visited their sites from Pinterest.

pinterest-analytics

Compared to the analytics available through 3rd party tools, the stats offered by Pinterest are basic. Premium tools such as Pinfluencer allow brands greater insight – for example, the ability to identify their most engaged followers and most influential pinners so they can focus their Pinterest activities as appropriate. However, if Pinterest is to offer ’sponsored’ sections as part of a monetisation strategy, it makes sense to roll out a tool that allows advertisers to measure the success of that activity in advance of launch. Pinterest is clearly learning from Tumblr’s mistakes in that regard – it’s rival network drew criticism for launching advertising formats without the means to measure their performance effectively.

The likelihood is that Pinterest has everything to gain and nothing to lose from the move. A survey back in August 2012 for Bizrate found that 70% of Pinterest’s users were motivated to use the network ‘to get inspiration on what to buy’ (compared to 17% of Facebook users), whilst a further 43% used the social network to ‘associate with retailers or brands with which I identify’ (24% for Facebook ). In addition, pins with prices get 36% more likes than those without, which all goes to demonstrate that Pinterest is the social network which most closely aligns the commercial goals of brands with the requirements of its users. The fact that Pinterest became Bottica’s leading social media referrer, assisting roughly 10% of sales, after the jewellery brand integrated ‘pinning’ buttons across its US website lends further weight to the argument.

And Pinterest is growing fast too – a recent Pew Internet study in the US found that pinning was almost as popular as Tweeting, with Pinterest attracting 15% of social media users compared to 16% for Twitter. In the UK, the base is small, less than 0.5m users but it’s growing fast – traffic to the site increased almost 800% between September 2011 and September 2012. The sample skews young (under 50), female (women are 5 times more likely to pin than men) and affluent (29% of UK users are in the highest income bracket). Combine this with the highly visual nature of the medium and you can see why a Pinterest presence is a must for premium fashion and lifestyle brands.

As well as painting a no doubt rosey picture regarding the amount of qualified traffic Pinterest is driving to brand websites, the new tools will also allow brands to hone their Pinterest content strategies by seeing which pins are popular overall, or even analysing popular pins on any given day and highlighting those on their website to create even more sharing.

However, many pinned images come from an array of unofficial sources that aren’t the brand’s website so marketer’s need to bear that in mind when using the analytics on offer to inform their content strategies.

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By: Carla Burgess

  • Nov
  • 1

Which Media Deliver the Best RoI?

Which_Media_Delivers_the_best_RoINo sooner had we reported recent research from ThinkBox which claimed that TV was the medium which delivered the greatest return on investment than that research is contradicted by a new study.

ThinkBox’s research, which analysed campaigns over a 5 year period, found that TV returned £1.70 in profit for every £1 spent, compared to £1.48 for radio, £1.40 for press, £1.06 for online static display and £0.45 for outdoor.

In addition,the study found that TV was the best medium for delivering sales uplift – 2.5 times more effective than it’s nearest rival, press.

However, the results of GfK’s Media Efficiency Panel, released last week, drew very different conclusions.

Their research tracked customer response to 8 major cross-media advertising campaigns from FMCG brands that ran in the last year, across a panel of 7,500 consumers. Sales uplift was measured in the 2-4 week period after the campaigns had finished.

Their findings contrasted sharply with those of Thinkbox’s study. In this case, TV delivered the worst RoI of the media measured – just 43p for every £1 spent.  The best performer was online activity, which delivered an average 75p for every £1 spent, following by press at 66p and Outdoor at 53p.

Online was also found to deliver the best sales uplift – 9% on average as compared to print’s 8%, TV’s 7% and outdoor’s 6%.

So how can 2 seemingly thorough pieces of research draw such widely differing conclusions? The differing scopes and methodologies offer some clues.

For example, ThinkBox’s research incorporated only static display: GfK’s included more effective formats like online video advertising and search, which would have boosted effectiveness scores. GfK’s research only measured short term RoI, measured over 2-4 weeks, something which is going to favour more responsive ad formats such as search and online display. In addition, GfK’s study focused on FMCG only, a sector which already heavily invests – and perhaps over-invests as the research would suggest – in TV. And finally, one could cynically suggest that one survey was sponsored by a body responsible for promoting commercial TV advertising and the other study was conducted in association with Google, a body with a vested interest in online marketing, so the results are compromised by their sponsors.

In truth, arguments about the absolute effectiveness of any medium are rather too general and largely unhelpful. Campaigns rarely happen in one medium, and it’s exceptionally difficult to isolate the impact of any particular medium when all media will be playing differing, but mutually supportive, roles in the purchase process. Understanding how media can work together to optimum effect is the question that most marketers should be striving to find the answers to, and it’s here that GfK’s research does unearth some interesting insights. 

For example, their findings did demonstrate that online activity can deliver substantial reach – in this case, 34% of their panel.  This doesn’t rival TV, with a 73% reach, but it is close to that delivered by press (39%) and exceeds that delivered by outdoor (29%).

But perhaps the most interesting finding was the incremental reach that online delivered. Between 25% and 63% of individuals exposed to at least one online ad were never exposed to the respective TV advertising and 46% of people exposed to YouTube and other online videos ads had no contact with the corresponding TV ads for that campaign.

In this case, online activity was not only found to play its traditional ’sharp end of the purchase funnel’ role of turning interest into action, but to expand the reach of campaigns into hard-to-reach, particularly younger, audiences who tend to escape traditional media activity.

The lesson from these findings is to think digital at the very earliest stages of planning – to understand how it can enhance and extend the reach of your campaign to audiences who may well not see any other channel executions – and not see it as purely a support for traditional media.

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By: Graham Painter

  • Mar
  • 29

Attribution Modelling: Beyond the Last Click

An Attribution Model from Forrester
An Attribution Model from Forrester

Attribution modelling has been in the news recently, with brands such as Boden crediting this approach to measuring RoI with transforming their view of how to invest their digital budget. 

But what precisely is ‘attribution modelling’?  And what role does it have to play in the marketing planning process for premium and luxuy brand marketers? 

Put simply, it’s about moving away from the approach which attributes all of the credit for a sale to the activity which generated the ‘last click’ and towards apportioning that credit to all online activity that played a part in moving the consumer down the purchase funnel. It’s about taking a more holistic view of digital marketing spend, and giving more credit to those activities – like display advertising and generic search terms – which are unlikely to be driving the final purchase, but are clearly playing an important role in the purchase process nonetheless. 

But it’s more than that. At its most sophisiticated it’s also about understanding what types of activity generate what types of customer. For example, shouldn’t activity that drives new customers get more credit than activity that retains existing ones. And shouldn’t activity that drives higher margin business get more credit than activity that drives lower margin business? 

The premis is simple and logical. The problem is, attribution modelling is not so simple to implement. 

To begin with, research needs to be undertaken to understand whether attribution modelling is relevant and what sort of model should be applied. For example, if a brand isn’t employing a mix of online channels to drive demand, it’s unlikely that attribution modelling can add much to its existing ‘last click’ analysis. The same applies if the purchase process is simple – attribution modelling is not going to add much value for all the effort involved. However, this is unlikely to be the case for most premium and luxury brands, where the nature of the purchase and the sophistication of the audience are likely to mean a long and complex buying process is going to be the norm. 

However, once the research is complete, there are plenty of tricky decisions to come. 

The first of those is to do with timing, namely how long is the product’s buying cycle?  Activity that happens before this ‘timing window’ needs to be discounted from the analysis.  For example, should searches or display banner views that took place 90 days prior to purchase be given credit or are these events unrelated to the final purchase decision because they were too distant from it? 

Secondly, decisions have to be made as to how to attribute the credit.  Should the first interaction with the brand’s marketing activity be given more credit as it prompted the customer to start the purchase journey?  Or should the last, that prompted the purchase? Or should all stages along the journey be treated equally? How much extra credit should be given to activity that was successful in generating new customers or more profitable customers? Should someone clicking a natural search result be given more weighting than a display ad view? 

The third challenge is implementation – unpicking the carefully constructed systems that have supported last click models of RoI and rebuilding them to support attribution modelling. And the complexity deepens the more systems that have to re-configured. 

So is attribution modelling worth all that effort? 

Well, it’s certainly not perfect. The whole process involves its fair share of educated guesswork and mistakes are going to be made. And marketers can’t fully understand what credit every stage in the process deserves because they can’t understand every customer – 2 identical purchase processes could have 2 very different triggers for purchase depending on what stimulated those individuals. And of course, we’re only attributing a fraction of the spend – offline activity such as press or magazine advertising isn’t part of this process as yet – although there’s no doubt that attribution models that incorporate offline channels are being looked at. 

But some understanding is better than none.  We all know the process of purchasing  premium and luxury goods is much more complex than one click = one purchase. So it’s time for our methods of measurement to catch up with our knowledge of the purchase process. 

Attribution modelling may be the start of a long road, but it’s better than the dead end that last click analysis represents.

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By: Carla Burgess

  • Sep
  • 30

Measurement System for Online Campaigns Launches in January

Luxury advertisers and their agencies will, at long last, have a reliable measurement system for planning online campaigns. UKOM, the UK online measurement company, has teamed up with The Nielsen Company to create an online audience planning system, to allow advertisers and agencies to create online campaigns which are able to target specific audience types. It is hoped and anticipated that this will include being able to target the more elusive, affluent profile audiences that luxury brands are so eager to reach with their online campaigns.

 Campaign Magazine reported  that the system will have a panel of at least 35,000 consumers, and has been approved with the backing of some of the UK’s largest advertisers and agency groups. The Audience Planning System, as it will be called, is set to launch in January 2010 and will  have the same industry approval standards applied to it as TV (Barb), radio (Rajar) and print media (NRS) audience systems. In supplying online audience data down to sites with as little as 50,000 unique visitors, the research should allow luxury and premium advertisers, or brands with smaller budgets such as fashion brands, to access with reliability, the best performing sites for their online audiences.

Guy Phillipson, the chief executive of the Internet Advertising Bureau and director of UKOM, said: “For the first time, advertisers and agencies will be able to confidently plan campaigns using industry-approved audience data comparable with traditional media, such as TV and press.

“I’m confident the UKOM Audience Planning System will transform the medium for brand advertisers.”

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By: Graham Painter