tag:econsultancy.com,2008:/topics/advertising Latest Advertising content from Econsultancy 2017-01-20T11:27:00+00:00 tag:econsultancy.com,2008:BlogPost/68724 2017-01-20T11:27:00+00:00 2017-01-20T11:27:00+00:00 Marketers plan Facebook audits following metrics faux pas Patricio Robles <p>More disturbing for Facebook is the fact that two-thirds of those surveyed indicated that they're questioning their Facebook ad investments.</p> <p>Advertiser Perceptions says that, outside of <a href="https://econsultancy.com/reports/paid-search-marketing-ppc-best-practice-guide/">Google paid search</a>, confidence in digital and social advertising platforms is well under 50% and, as it relates to Facebook, advertiser concerns may be largely due to <a href="https://econsultancy.com/blog/68332-should-marketers-be-more-concerned-about-facebook-s-video-metrics-faux-pas">a string of revelations about inaccuracies</a> with the company's ad metrics.</p> <h3>Move fast and break things</h3> <p>While Facebook says that those faux pas - which resulted in a number of metrics being inaccurately reported, in some cases by substantial amounts - didn't impact billing for ads, a number of companies <a href="http://www.mediapost.com/publications/article/293221/facebook-hit-with-new-lawsuit-over-inflated-video.html">have sued Facebook</a>, claiming that the errors influenced their decisions to invest in Facebook.</p> <p>Even if Facebook is successful in defending against the lawsuits, the company, which once popularized the mantra "move fast and break things," can ill afford to see an erosion of advertiser faith as younger competitors, namely Snapchat, more aggressively vie for social ad dollars. Even more importantly, if advertisers lose faith in Facebook, it could poison the entire market for social ads, driving advertisers to shift dollars to other digital channels.</p> <p>Indeed, Advertiser Perceptions says that among advertisers planning to up their spend with Facebook and Google, only 8% plan to up their spend with Facebook but not Google, while 36% plan to up their spend with Google but not Facebook.</p> <p>Of course, what's challenging and potentially problematic for Facebook isn't necessarily bad for advertisers. Few today doubt the viability of social ads but as social advertising reaches a greater level of maturity and advertisers have more significant experience and data behind their efforts, it is absolutely appropriate for them to start paying closer attention to and evaluating the efficacy of their campaigns.</p> <p>In many cases, independent audits are worthwhile, and as Facebook sees advertiser scrutiny increase, it might eventually be forced to relent and offer greater transparency, such as third-party tagging, which <a href="https://adexchanger.com/online-advertising/facebook-and-groupm-tussle-on-third-party-viewability-verification/">has to date been a source of tension</a> between the company and advertisers.</p> <p><em>To brush up your skills in this area, check out these Econsultancy resources:</em></p> <ul> <li><a href="https://econsultancy.com/reports/social-media-best-practice-guide/"><em>Social Media Best Practice Guide</em></a></li> <li><a href="https://econsultancy.com/training/courses/social-media-paid-advertising/"><em>Social Media Paid Advertising Training</em></a></li> </ul> tag:econsultancy.com,2008:BlogPost/68702 2017-01-20T01:00:00+00:00 2017-01-20T01:00:00+00:00 Three bold marketing technology predictions for 2017 Jeff Rajeck <p>Econsultancy has <a href="https://econsultancy.com/blog/68648-five-predictions-for-conversion-rate-optimisation-cro-in-2017/">several posts</a> which make <a href="https://econsultancy.com/blog/68661-five-trends-which-will-define-data-driven-marketing-in-2017/">bold statements</a> about the future of digital, but to change things up slightly we asked a few industry experts to chime in with their vision of what we will see in 2017 as well.</p> <p>In the brief video, Antonia Edmunds from IBM Marketing Cloud offers her views on what marketers should expect in the coming year.</p> <p><iframe src="https://www.youtube.com/embed/0xm2T518_eU?wmode=transparent" width="560" height="315"></iframe></p> <p>While the trends Ms. Edmunds mentions may not have achieved mass acceptance yet, it seems that marketers have been talking about each of these topics over the past year.</p> <p>Below are summaries of each of the points and links to further reading on the topics.</p> <h3>1. Cognitive marketing will give marketers better customer insights</h3> <p>Cognitive marketing, or marketing which uses technology that mimics the human brain to improve performance, was just starting to emerge as a concept in 2016. <a href="https://martechtoday.com/now-entering-age-cognitive-marketing-169117">Industry experts feel</a> that there will soon be an 'explosion' in the number of marketing systems which use it, though.</p> <p>When <a href="https://econsultancy.com/blog/68634-three-ways-brands-will-use-cognitive-marketing/">the topic was discussed at an Econsultancy event in Delhi</a>, participants came up with three ways in which cognitive marketing could be used to help them understand their customers better and improve their performance.</p> <h4>Segment audiences in new ways</h4> <p>Cognitive-based systems will be better at finding behavioural characteristics among people who appear to be very different.</p> <h4>Personalise content</h4> <p>Marketers using cognitive technology would be able to redesign messaging so that virtually every consumer saw something different, and something which was more relevant to them.</p> <p><img src="https://assets.econsultancy.com/images/0008/2369/delhi2.jpg" alt="" width="800" height="533"></p> <h4>Help customers make better decisions</h4> <p>By using massive computing power and large data sets, cognitive marketing systems will be able to identify unmet and unstated customer needs and help brands produce better offers and product guidance.</p> <h3>2. Marketers will shift from siloed channel strategies to cross-channel engagement</h3> <p>Marketers needed little prompting in 2016 to discuss their plans for how they were tackling the difficult task of delivering cross-channel marketing.</p> <p>At <a href="https://econsultancy.com/blog/68307-three-things-marketers-must-do-to-deliver-a-brilliant-omnichannel-experience/">a recent event in Melbourne</a>, marketers came up with <strong>three main points about what it will take for brands to follow consumer behaviour and become truly omnichannel.</strong></p> <h4>Identify data sources and break down silos</h4> <p>Effective cross-channel marketing is 'all about the data'. Yet marketers felt that one of the most important steps toward increased cross-channel engagement was to have access to all of the channel performance data.</p> <p>Without it, they would not be able to measure performance and improve.</p> <h4>Train up marketers so they can integrate systems</h4> <p>Another thing which brands need to do for cross-channel marketing is to ensure that their team knows how to use the technology they already have.  </p> <p>Participants indicated that <strong>there is a particularly big knowledge gap between what marketers are familiar with today and what is necessary to map the customer journey.</strong></p> <p><img src="https://assets.econsultancy.com/images/0007/9329/j2.jpg" alt="" width="800" height="533"></p> <h4>Take a unified approach to offline and online marketing</h4> <p>Finally, the brand needs to have a unified approach to its messaging, both online and offline.  </p> <p>As one delegate said, <strong>there is little point advertising to change perception of the brand on one medium and then not to be able to deliver that experience on the other.</strong></p> <h3>3. Marketing and ad technologies will converge</h3> <p>Predicted for some time now, it seems that combining <a href="https://econsultancy.com/blog/65212-what-is-marketing-automation-and-why-do-you-need-it/">marketing automation</a> with ad buying may finally happen in 2017. Benefits of doing so include being able to leverage data between web, email, and ad platforms to improve performance and customer experience.</p> <p><a href="https://econsultancy.com/blog/68665-three-keys-to-digital-advertising-success-in-2017/">At Digital Cream Singapore</a>, attendees said that there are <strong>three things marketers needed before marketing and advertising could be fully integrated.</strong></p> <h4>A cross-market ad buying strategy</h4> <p>For companies with marketing teams across geographies, marketers need to centralise ad spending before they integrate marketing.  </p> <p>This is particularly difficult in Asia-Pacific and as such many brands in the region are relying solely on the 'ad duopoly', Google and Facebook, for their advertising.</p> <h4>A single view of the customer</h4> <p>Most marketing teams now typically have data spread across many systems. So in order to merge marketing and advertising, they need to combine data to have a single, cross-organisational view of the customer.</p> <p>Doing so will make it much easier to share attributes, interests, and behaviours between ad and marketing automation platforms.</p> <p><img src="https://assets.econsultancy.com/images/0008/2648/5.jpg" alt="" width="800" height="533"></p> <h4>An attribution model</h4> <p>Finally, in order to have one technology stack, marketers felt that they need to agree on how to attribute credit for conversions for each step of the customer journey.</p> <p>Doing so is much more difficult than it sounds, so <strong>many marketers end up using last click or a 'fluid' attribution model which is changed periodically based on data.</strong></p> <p>It seems, therefore, that there are quite a few precursors required for these predictions to come true. One common requirement, though, is the need for a common data platform so that marketers can share data among themselves as well as with the organisation as a whole.  </p> <p>Breaking down data siloes should, therefore, be on everyone's wish list in 2017!</p> tag:econsultancy.com,2008:BlogPost/68687 2017-01-12T10:03:18+00:00 2017-01-12T10:03:18+00:00 My nightmare trying to understand header bidding Ben Davis <p>I understand the theory and the different components of the <a href="https://econsultancy.com/blog/67287-eight-ways-to-improve-the-real-time-bidding-ecosystem/">RTB ecosystem</a>, but after reading countless articles it seems that the reality is a complete mess.</p> <p>And a thoroughly Kafkaesque mess at that. Okay, this isn't exactly news, but I thought that rather than write about header bidding, it might be more interesting to write the story of a layman trying to understand it all.</p> <h3>This much I knew</h3> <p>Real-time bidding is the process of selling advertising space via an open ad exchange auction.</p> <p>These open auctions are where publishers often sell their less valuable inventory, after the more sought after spots have been sold directly to preferred advertisers (through programmatic direct, private marketplaces or preferred deal).</p> <p>For a simple explanation of real-time bidding and programmatic direct, you can check out <a href="https://econsultancy.com/blog/65677-a-super-accessible-beginner-s-guide-to-programmatic-buying-and-rtb/">Christopher Ratcliff's Beginners Guide</a>.</p> <p>Essentially, RTB allows advertisers to bid on different users (from pre-defined demographics) that pitch up at different types of web content. Successful bidders pay the second highest price (so they don't lose out if they bid far more than everyone else) and their adverts are served to the user.</p> <p>This much, I knew. And it made sense to me.</p> <h3>Don't go chasing waterfalls</h3> <p>But when I tried to read up on the inefficiencies of RTB (which led to the development of header bidding), things started to get confusing.</p> <p>Lots of people seemed to mention an inefficient waterfall process, whereby unsold inventory is offered by the ad server to one ad exchange after another, the top-ranked one first (estimating what the exchange can bring in), then passed down to lower ranked exchanges if the inventory is not sold.</p> <p>This ranking of so-called 'demand sources' is apparently one of the problems with traditional RTB. This ranking doesn't take real-time demand into account, so the low-ranked exchanges, though perhaps smaller, may have stumped up a higher bid (and so publishers lose out).</p> <p>Google's Doubleclick for Publishers is a commonly used ad server, which gives priority to (surprise, surprise) Google's ad exchange, AdX, which can pip other bidders.</p> <p>Conceptually, I understand this, but then I thought, what about supplier side platforms (SSPs), where do they come in?</p> <h3>But what about SSPs?</h3> <p>It was my understanding that SSPs were designed to offer publisher inventory to multiple ad exchanges and provide tools with which they can optimise their yield.</p> <p>SSPs are meant to make everything easier. So, why all this waterfalling and inefficiency?</p> <p>I delved into definitions and more theories and found that publishers not only have waterfalls of ad exchanges, but they waterfall SSPs, too.</p> <p>This seems like complicated madness. Publishers push inventory through their first SSP at a high price, dropping the price if it doesn't sell and pushing through the next SSP.</p> <p>Aside from the publisher-side headache of cascading bids through these multiple SSPs (which were supposed to simplify things), there's the slightly dubious idea that the exact same inventory is priced differently depending on where an advertiser buys it.</p> <p>If I'm honest, at this point I was still a bit confused about what was an SSP and what was an ad exchange. SSPs are routinely referred to as 'demand sources' (I thought they were for selling?) and I had to do plenty of Googling to find out how certain platforms are described.</p> <p>As those in the know will tell you, there is now little differentiation between SSPs and ad exchanges. They both aggregate inventory, but the difference is that SSPs should put more focus on publisher value.</p> <p>However, each adtech platform out there has sought to add functionality, meaning that SSPs and ad exchanges are almost the same thing. Ad exchanges included SSP functionality - Google's ad exchange did this back in 2011 (rolling SSP Admeld into its platform).</p> <p>So, the bottom line is that SSPs are just like ad exchanges, and they don't offer complete access to the market, because all the different SSPs are competing and want to protect their demand sources, which fragments everything.</p> <h3>Hang on, you still haven't told us what header bidding is!?</h3> <p>Header bidding is some extra JavaScript that allows buyers and ad exchanges to submit their bids before page load, hence before the ad server is called.</p> <p>So, all the bids come in at the same time and this can mean a higher price is achieved. The publishers can even let the open exchange beat a direct-sold impression, if the price fits. </p> <p>There's a debate about whether header bidding decreases or increases latency - its advocates say that because all bids come in at the same time, there's less chance of a time-out (when the publisher would fill the spot with its own internal ads).</p> <p>However, others think header bidding increases complexity and also latency (notably Google, which doesn't exactly stand to benefit from header bidding, given it breaks the dominance of AdX).</p> <h3>Google is fighting back though</h3> <p>Google has rolled out First Look as its own attempt to solve the same problem as header bidding does.</p> <p>Publishers using the Doubleclick ad server can use its Dynamic Allocation tool to see in real-time how much media buyers within the Google ecosystem are willing to pay for an impression.</p> <h3>What's my overall feeling after such a nightmare?</h3> <p>SSPs should talk to each other, but they don't and that's a problem for publishers who want to make the most of their inventory.</p> <p>Some very brief thoughts on my nightmare:</p> <ol> <li>Why aren't adtech companies better at explaining what they are and how the process works? Perhaps they don't want to confuse people.</li> <li>I realise that the internet isn't really a democracy, but until some of these processes are replaced by a more elegant solution, doesn't the complexity mean that bad practices take longer to come to light?</li> <li>How can we expect fraud and viewability to be tackled without greater integration?</li> <li>There's a skills shortage in programmatic - the industry needs to get better at explaining all this stuff.</li> <li>No wonder publishers are investigating bespoke and native formats.</li> </ol> <p>A big caveat: My knowledge is limited. That's the whole point of this article. If, reader, you find any errors in what I have written above, please set me straight in the comments below.</p> <p><em>For more on this topic, check out these Econsultancy resources:</em></p> <ul> <li><a href="https://econsultancy.com/reports/the-cmo-s-guide-to-programmatic/"><em>The CMO's Guide to Programmatic</em></a></li> <li><a href="https://econsultancy.com/training/courses/programmatic/"><em>Programmatic Training Course</em></a></li> </ul> tag:econsultancy.com,2008:BlogPost/68682 2017-01-09T11:19:08+00:00 2017-01-09T11:19:08+00:00 Programmatic 101: What are user scoring and propensity modelling? Ben Davis <ul> <li>probability scoring</li> <li>best-next-action modelling</li> <li>continuous scoring algorithms</li> <li>algorithmic attribution</li> <li>lookalike modelling</li> <li>predictive analytics</li> <li>customer behaviour scoring</li> <li>propensity score matching</li> </ul> <p>However you refer to it, propensity modelling is changing dramatically as machine learning is lending its weight to improving the efficiency of advertising and marketing.</p> <p>Indeed, Chris O'Hara from Krux refers to this revolution in data science as the most important trend in programmatic advertising (see <a href="https://econsultancy.com/blog/68650-the-future-of-programmatic-2017-and-beyond/">Econsultancy's programmatic trends for 2017</a>). Here are a few of Chris's most succinct comments on the issue:</p> <ul> <li>"Getting a programmatic edge means...being better than your competitors at knowing where and how much to bid..."</li> <li>"...most marketers and agencies have little native competence in user scoring and propensity modeling..."</li> <li>"[But] we are starting to see...platforms that embed machine learning and artificial intelligence into their user interfaces in such a way that business users can access such capabilities without...having statistical abilities."</li> </ul> <h3>So, what is it? </h3> <p>Advertisers want to use the profusion of online data to their advantage, creating a model of certain consumers in an effort to predict who will respond to specific messages, or indeed buy a particular product.</p> <p>Data science now allows for meaning to be found in enormous datasets, which is essentially what machine learning does, a form of AI that can 'learn' from each new interaction between consumer and message.</p> <p>Propensity modelling chiefly refers to the modelling of a person's propensity to click on an ad or to convert (once they have clicked). Whilst this type of modelling has historically been applied to a company's own customer base in order to predict who is likely to churn for example, or which sales lead may bear fruit, it is now being used on a wider scale online to target unknown consumers, too.</p> <p>This technique helps to plan ad impressions based on a whole range of variables and it can now be conducted in real-time during the bidding process for online media (through integration of data management platforms and demand side platforms).</p> <p>Advertisers can target different behaviours and demographics, or create segments based on various personas of their current customers (high value buyers, discount buyers, browsers etc.) and these segments can be used in lookalike modelling to define what traits to look for in a larger data set of visitors.</p> <p>Understandably, those companies with rich <a href="https://econsultancy.com/blog/67674-what-are-first-second-and-third-party-data/">first-party data</a> are better placed when it comes to accurately modelling potential customers, because they can describe a more accurate portrait of their current customers.</p> <p>The increased ability to track customers across multiple online channels and, via <a href="https://econsultancy.com/blog/67995-mobile-programmatic-the-basics-that-cmos-need-to-know/">a device graph</a>, from desktop to mobile, means that propensity modelling can be brought to bear on more than just display advertising.</p> <h3>Scoring across more than just display</h3> <p>In our 2017 programmatic trends roundup, Chris O'Hara picks up on the complexity of scoring across multiple channels:</p> <p>"[The use of machine-learning powered platforms] was more straightforward when it was just available to display marketers seeking to manage bid pricing thresholds on cookies.</p> <p>"[However,] today, marketers are increasingly using data management technology to map users across their device graph, and expect the ability to score users against their interactions across every addressable channel—not just 'display' advertising, but also email, commerce, and website experiences.</p> <p>"To do this correctly, marketers need to map users to all their devices and be able to store highly granular attribute data going back longer than the life of the typical cookie.</p> <p>"These are “big data” problems that require highly advanced technology. Much of what is happening today is ad hoc reporting in spreadsheets that drives manual optimizations across many different buying platforms."</p> <p>In the long run of course, marketers are trying to map the customer journey to purchase, and to tickle as many consumers along it as possible. For example, marketers want to understand at which point in the customer journey particular content versions and formats have the most positive impact on the decision to purchase.</p> <p>However, propensity modelling and increased targeting doesn't, of course, mean 100% efficiency. Quality of ad placement is vitally important, and private marketplaces allow advertisers to take part in invite-only auctions for the best ad spots that will give the best return.</p> <p><em>For a full overview of programmatic advertising, read <a href="https://econsultancy.com/reports/the-cmo-s-guide-to-programmatic/">The CMO's Guide to Programmatic</a> or book onto our <a href="https://econsultancy.com/training/courses/programmatic/">Programmatic Training Course</a>.<br></em></p> tag:econsultancy.com,2008:BlogPost/68671 2017-01-04T03:30:00+00:00 2017-01-04T03:30:00+00:00 The best APAC digital marketing stats from December 2016 Ben Davis <h3>30% of online sales in SE Asia through social</h3> <p>That astonishing estimate comes from consulting firm Bain &amp; Co and is reported <a href="http://www.wsj.com/articles/where-facebook-and-instagram-are-about-shopping-1481023577">in the Wall Street Journal</a>.</p> <p>The success of social sales is thought to be due to a profusion of SMEs using new social messaging functionality to support ecommerce (such as Facebook, Line and Instagram) and the lack of a dominant ecommerce player such as Amazon.</p> <p>In 2015, Facebook rolled out its <a href="https://www.facebook.com/business/news/facebooks-new-shop-section-in-pages-lets-products-take-centre-stage">Shop section</a> in Southeast Asia, allowing those who run business pages to feature products. Messenger works in tandem with Shop, allowing businesses to showcase and discuss their products with customers.</p> <p>Line offers a tool for SMEs in the region called Line@. Promotions are broadcast using the tool and customers then message a company to make a purchase.</p> <p><img src="https://assets.econsultancy.com/images/0008/2708/nix.jpg" alt="facebook shop" width="500"></p> <p><em>Facebook Shop</em></p> <h3>Australia bricks-and-mortar boom</h3> <p><a href="http://www.roymorgan.com/findings/7075-retailtainment-effect-aussies-made-90-million-more-trips-to-shops-last-year-201612020900">A study by Roy Morgan Research</a> of Australians aged 14+ and their shoping habits has shown an increase in bricks-and-mortar retail store visits in financial year 2015-2016.</p> <p>There were 90m more visits, year on year, the first increase for five years. A total of 1.43bn store visits were made, with clothing, hardware, discount and department stores enjoying increases.</p> <p>Newsagents were the only stores to see a decrease in footfall, linked to the decline of print news. Music store footfall plateaued.</p> <p>Improved customer experience in-store leading to more enjoyable shopping trips is thought to be one of the factors in this turn around in footfall.</p> <p><img src="https://assets.econsultancy.com/images/0008/2699/morgan.jpg" alt="increase in australian footfall" width="615"></p> <p><em>Roy Morgan, July 2014-June 2016. Base: Australians 14+</em></p> <h3>Video ads in SE Asia are too long</h3> <p>Completion rates for 30-second video spots in Southeast Asia are 20% shorter than those for 15-second videos.</p> <p>Research by TubeMogul (<a href="http://www.mumbrella.asia/2016/12/fb-marketers-obsession-30-second-digital-spots-consumers-reaching-skip-button/">reported in Mumbrella</a>) shows that marketers in the region haven't moved towards shorter spots yet, in the way that those in the US, UK and Australia have.</p> <p>The trend is particularly noticeable in food and drink, where the research was focused, with 94% of Southeast Asian marketers investing in 30-second spots.</p> <p>This is, in part, a hangover from longer TV creative. Shorter video is seen as more suitable for mobile views.</p> <p><em>Southeast Asian food and drink video ad split and completion</em></p> <p><img src="https://assets.econsultancy.com/images/0008/2709/ad_length.png" alt="video ad completion" width="372" height="315"></p> <h3>Netflix surges in Australia</h3> <p>Netflix subscriber numbers in Australia are now comparable to rival Foxtel. Roy Morgan Research figures show that 750,000 subscribers have been added since May 2016.</p> <p>In November, 5.8m Australians aged 14+ had access to Netflix in their homes (that's 29% of the population), through 2.2m subscriptions (<a href="http://www.bandt.com.au/media/study-5-75-million-aussies-now-netflix-not-watch-much">more from B&amp;T</a>).</p> <p>The research showed that time spent watching Netflix is comparatively low:</p> <ul> <li>42% of Netflix subscribers streamed less than three hours a week.</li> <li>16% didn't watch anything at all.</li> </ul> <p>However, a majority of Foxtel subscribers watched at least eight hours a week of content.</p> <p><img src="https://assets.econsultancy.com/images/0008/2700/netflix_time.png" alt="netflix engagement in australia" width="615"></p> <h3>Indian internet users to hit 600m by 2020</h3> <p>The number of internet users in India will hit 600m by 2020, almost double the current number, according to <a href="http://www.assocham.org/newsdetail.php?id=6070">a report by ASSOCHAM and Deloitte</a>.</p> <p>The current level of internet penetration in India is 27%, some way behind China's 50.3%.</p> <p>India has 240m smartphone subscribers but only 31,000 WiFi hotspots. That's a ratio of around one hotspot to 8,000 smartphones, far below the global average of one hotspot to 150 smartphones, with the report highlighting 55,000 villages currently without mobile connectivity.</p> <h3>Digital advertising makes up almost half of total Australian ad spend</h3> <p>Online ad spend was 48% of total ad spend in Australia for H1 2016, according to a Commercial Economic Advisory of Australia (CEASA) statement.</p> <p><a href="https://www.iabaustralia.com.au/news-and-updates/iab-press-releases/item/22-iab-press-releases/2233-fmcg-brands-leading-the-way-with-digital-video-to-deliver-brand-uplift">A recent IAB and PwC report</a> estimated online ad spend at more than A$1.88bn in Q3 2016, a 20.3% increase year-on-year The report also detailed change in spend in formats with classifieds up 13.4%, search and directories up 22.8% and general display up 21%.</p> <p>Video is in the ascendancy, with FMCG advertisers now spending roughly three times as much on video as they are on general display.</p> <p><em>Chart showing general display advertising expenditure by sector as percentage of total display ad spend</em></p> <p><img src="https://assets.econsultancy.com/images/0008/2701/change_in_ad_spend_share.png" alt="ad spend share by category" width="615"></p> <h3>Ad spend down in Thailand after death of king</h3> <p>Ad spend in Thailand fell by 42.6% in November after the death of King Bhumibol Adulyadej.</p> <p>Nielsen Thailand data (<a href="http://www.nationmultimedia.com/news/business/EconomyAndTourism/30301800">reported in The Nation</a>) show ad spend of Bt 6.11bn, down from Bt 10.65bn in November 2015.</p> <p>Television, radio and print account for more than 80% of ad spend in Thailand. All three have declined over January to November 2016, compared with the same period last year.</p> <h3>Australian multiscreening</h3> <p>The average number of connected devices (excluding TVs) per household has increased from 3.9 to 4.5 over the last four years.</p> <p><a href="http://www.oztam.com.au/documents/Other/Australian%20Multi%20Screen%20Report%20Q3%202016%20FINAL.pdf">Oztam's Australian Multi-Screen Report</a> shows, however, that the majority of viewing still takes place on the TV set.</p> <p><img src="https://assets.econsultancy.com/images/0008/2704/oz_screens.png" alt="oz screen time" width="615"></p> <p><em>Source: Estimates based on OzTAM Metro and Regional TAM Establishment Surveys.</em></p> <h3>Mobile usage surpasses TV in India</h3> <p>Time spent on smartphones in India has surpassed other media, according to <a href="http://www.ptinews.com/pressrelease/21945_press-subKantar-IMRB---MMA-Launch-a-Comprehensive-Report-on-Smartphone-and-Feature-Phone-Trends">a report from the Mobile Marketing Association and Kantar IMRB</a>.</p> <p>The average consumer spent three hours a day on their smartphones in 2016, a 55% increase on the previous year.</p> tag:econsultancy.com,2008:BlogPost/68665 2017-01-04T01:00:00+00:00 2017-01-04T01:00:00+00:00 Three keys to digital advertising success in 2017 Jeff Rajeck <p>Some the changes which have been covered extensively include: </p> <ul> <li> <strong>Platforms</strong> - some which have risen (hello Snapchat) and others, fallen (Meerkat, RIP).</li> <li> <strong>Header bidding</strong> - which has become a significant challenger to traditional ad exchanges.</li> <li> <strong>Advertising on messaging apps</strong> - which is tipped to bring big changes to the ad market.</li> </ul> <p> At Digital Cream Singapore, we spoke with dozens of client-side marketers about these changes and how they affect their agenda for the coming year. </p> <p>Surprisingly, though, <strong>most brand marketers were less concerned about the latest technology or platforms and </strong><strong>more worried about how they will use digital advertising to deliver value to the business. </strong></p> <p>To make that happen, participants on the day identified three things which they consider as priorities if they are to bring success in the coming year.</p> <h3>1) A single view of the customer</h3> <p>Attendees felt that most organisations have plenty of customer data. Nearly everyone has a CRM with customer attributes, most use web analytics to capture on-site user behaviour, and now a significant number have implemented a data management platform to understand what their customers do on other sites.</p> <p>The problem for marketers, though, is that customer data is spread across several systems. As a result, it is difficult to join up the data and obtain a single view of the customer which links their attributes, interests, and behaviour.</p> <p>Participants felt that fragmented customer data is particularly problematic for digital advertising. As digital ad platforms need data for segmenting, targeting, and positioning, marketers without a single view of the customer are not able to exploit opportunities and deliver the best value to the business.</p> <p><strong><img src="https://assets.econsultancy.com/images/0008/2647/3.jpg" alt="" width="800" height="533"></strong></p> <p>One technology which helps marketers obtain a single customer view is a <strong>'customer data platform' (CDP)</strong>.</p> <p>A CDP is a system which:</p> <ul> <li>Combines data from multiple sources.</li> <li>Lets marketers build customer profiles.</li> <li>Delivers messaging across multiple platforms.</li> <li>Uses decision-making algorithms to optimize performance.</li> </ul> <p>While CDPs sound promising, they are relatively new and so marketers will need to conduct more research before they are widely-deployed.</p> <p>More information about CDPs is available <a href="http://customerexperiencematrix.blogspot.sg/2015/01/customer-data-platforms-revisited.htm">here</a> and a list of vendors is available via the <a href="http://www.cdpinstitute.org/">CDP Institute</a>.</p> <h3>2) A cross-market ad buying strategy</h3> <p>Another issue client-side marketers hope to solve in 2017 is how to buy ads programmatically across different markets.</p> <p><strong>The problem marketers face is that different countries usually have different ad platforms</strong>. Marketing managers struggle with becoming familiar with each of them in order to train the regional teams.</p> <p><strong>Some participants avoid this issue by relying solely on the 'ad duopoly', Google and Facebook</strong>, to cover multiple markets. Others, however, find this approach limiting and feel compelled to use additional programmatic platforms to reach more consumers.</p> <p><img src="https://assets.econsultancy.com/images/0008/2648/5.jpg" alt="" width="800" height="533"></p> <p>Another issue raised was that <strong>Asia-Pacific does not have many third-party measurement services</strong> which help them avoid bot fraud, fraudulent inventory, and unviewable ads. This was particularly a problem for advertisers who operate in China.</p> <p>Delegates offered few ideas into what managers can do about this besides upgrading ad-buying technology and ensuring that regional marketers keep a closer eye on local ad networks.</p> <p>According to a 2016 <a href="https://www.exchangewire.com/bidswitch-report/">BidSwitch survey of buy-side technology firms in Asia-Pacific</a>, the problem isn't going away soon - and indeed may get worse. Nearly half (45%) of respondents indicated that <strong>there will be more programmatic technology companies in APAC over the next three years.</strong></p> <p><img src="https://assets.econsultancy.com/images/0008/2646/graph.png" alt="" width="800" height="517"></p> <h3>3) An attribution model</h3> <p>Finally, the most frequently-discussed item on the digital advertiser 'wish list' for 2017 was marketing attribution.</p> <p>Having an agreed method for attributing marketing success to different channels has eluded most marketing teams, participants noted. The issues they face include: </p> <ul> <li>Obtaining the view and click data from all of the channels.</li> <li>Calculating the value of each touchpoint.</li> <li>Using the model to dictate media spend.</li> <li>Understanding of the customer journey.</li> </ul> <p><img src="https://assets.econsultancy.com/images/0008/2649/4.jpg" alt="" width="800" height="533"></p> <p>One delegate said that<strong> their marketing team overcame some of these issues by implementing a 'fluid' attribution model</strong>. Their approach was to have all stakeholders meet regularly, review ad performance data and, based on hard data, adjust the attribution model appropriately.</p> <p>While not perfect,<strong> introducing flexibility into the model reduced the stakes for all parties as nothing was 'fixed in concrete'</strong>. This, in turn reduced the politics around adopting a model and led to quicker acceptance.</p> <p>Still, many attendees felt that they did not yet know enough to develop an attribution model and so 2017 was going to be another year of learning.</p> <h3>A word of thanks </h3> <p>Econsultancy would like to thank all of the marketers who participated on the day and the moderator for the Online Advertising table, <strong>Stephanie Myers, Senior Vice President of Digital Marketing at HSBC.</strong></p> <p>We hope to see you all at future Singapore Econsultancy events!</p> <p><img src="https://assets.econsultancy.com/images/0008/2650/end.jpg" alt="" width="800" height="533"></p> tag:econsultancy.com,2008:BlogPost/68650 2016-12-21T11:00:00+00:00 2016-12-21T11:00:00+00:00 The future of programmatic: 2017 and beyond Ben Davis <p>Thanks go to our trio of experts for providing some cogent analysis:</p> <ul> <li>Chris O'Hara, Head of Global Marketing, Krux (Salesforce DMP)</li> <li>Emily Macdonald, Head of Programmatic, International, DigitasLBi</li> <li>Tom Wright, Head of Programmatic, Tomorrow TTH</li> </ul> <h3>The coming democratization of data science</h3> <p style="font-weight: normal;"><strong>Chris O'Hara, Head of Global Marketing, Krux:</strong></p> <p style="font-weight: normal;">If we’ve learned anything over the last several years in programmatic it’s that—in a world of commoditized inventory and <a href="https://econsultancy.com/blog/67674-what-are-first-second-and-third-party-data/">3rd party data</a>—getting a programmatic edge requires diving deep into the data for insights.</p> <p style="font-weight: normal;">That means being better than your competitors at knowing where and how much to bid, which correlates directly with an organization’s skill at data science.</p> <p style="font-weight: normal;">The problem is that most marketers and agencies have little native competence in user scoring and propensity modeling—and even if you had the budget to hire a dozen data scientists, they are incredibly hard to find. </p> <p style="font-weight: normal;">What we are starting to see today are platforms that embed machine learning and artificial intelligence into their user interfaces in such a way that business users can access such capabilities without writing algorithms, using separate data visualization platforms, or having statistical abilities. </p> <p style="font-weight: normal;">This capability was more straightforward when it was just available to display marketers seeking to manage bid pricing thresholds on cookies.</p> <p style="font-weight: normal;">[However,] today, marketers are increasingly using data management technology to map users across their device graph, and expect the ability to score users against their interactions across every addressable channel—not just “display” advertising, but also email, commerce, and website experiences.  </p> <p style="font-weight: normal;">To do this correctly, marketers need to map users to all their devices and be able to store highly granular attribute data going back longer than the life of the typical cookie.</p> <p style="font-weight: normal;">These are “big data” problems that require highly advanced technology. Much of what is happening today is ad hoc reporting in spreadsheets that drives manual optimizations across many different buying platforms. </p> <p style="font-weight: normal;">In 2017, we will start to see the evolution of data science applications as they become more embedded in platforms—<a href="https://econsultancy.com/blog/68496-10-examples-of-ai-powered-marketing-software/">“AI layers” that leverage machine learning</a> within platforms, and make things like user scoring, propensity modeling, lifetime value (LTA) analysis, and next-best action recommendations less manual and more automated. </p> <h3><strong>The march of martech</strong></h3> <p style="font-weight: normal;"><strong>Emily Macdonald</strong><strong>, Head of Programmatic, International, DigitasLBi</strong></p> <p style="font-weight: normal;">No-one could ignore 2016’s massive spending spree by martech companies like Oracle, IBM and Adobe, as they grew their market share via acquisitions, plugged tech stack gaps and invested in areas such as Artificial Intelligence for smart CRM.</p> <p style="font-weight: normal;">Notably, these acquisitions included programmatic adtech companies such as TubeMogul and Krux, making programmatic a key part of the conversation.</p> <p style="font-weight: normal;">[These martech companies offer] brand marketers a fully integrated control centre that coordinates, unifies and simplifies data across all consumer touch points to optimally inform marketing, media activation strategies and spend. </p> <p style="font-weight: normal;">As the martech focuses on quickly integrating acquisitions and retaining experts, they are also pushing change.</p> <p style="font-weight: normal;">We see a desire by some brands and integrated agencies to optimise both operational and performance efficiencies with data, creative, CRM, paid and earned media all under one roof.</p> <h3>Data science is the new measurement </h3> <p><strong>Chris O'Hara:</strong></p> <p>An ongoing challenge in programmatic is measurement.</p> <p>Marketers tend to rely on various industry-accepted currencies to validate their media investments (Comscore for viewability, Nielsen to measure reach into a certain demographic, or Datalogix for purchase data).</p> <p>These are fine yardsticks, but we are starting to see marketers desire a more granular, less panel-based, approach to measurement. </p> <p>Marketers have been quick to embrace enterprise data management over the last several years, and are now starting to build “consumer data platforms” (CDPs) to align their entire organizational data around a single identifier for their customers.</p> <p>As they own more of their own first-party data asset, marketers can now look across the entirety of their data—not just from display advertising, but also from email, IoT, commerce, app, website, social, and search—and begin to get a universal view of cross-channel performance.</p> <p>This granularity of disparate data, available to query in a single platform, and tied to cross-device user identifier, now presents the opportunity for finer-grained measurement and is the first, important step towards changing the attribution game. </p> <p>This means that the ability to query and make sense from a large scale of data using machine learning and algorithmic approaches (essentially called “data science”) is the new basis for measurement moving forward. </p> <p>Will we see marketers moving away from established, traditional measurement currencies in 2017?</p> <p>Probably not, but we will certainly see enterprise marketers leverage their newly acquired data capabilities to challenge the status quo, and supplement the measurement they are currently doing.</p> <h3>Rethinking client-agency relationships</h3> <p style="font-weight: normal;"><strong>Emily Macdonald:</strong></p> <p style="font-weight: normal;">In 2016, the role of the media agency came into question.</p> <p style="font-weight: normal;">As more brands look to take control and invest in or restructure for the omnichannel vision, we can see the dynamic of the client-agency relationship shifting.</p> <p style="font-weight: normal;">Along with the need for greater transparency, expertise and sharing of knowledge, it’s also essential to have a clear partnership focused on putting the personalisation and synchronisation of consumer messaging at the centre of everything.</p> <p style="font-weight: normal;">Brands need to rethink consumer engagement and storytelling with the optimised blend of data, technology, media and creative, rather than operating in brand marketing or creative and media agency silos.</p> <p style="font-weight: normal;">This applies not just to big brand marketers wishing to take programmatic in-house and hiring programmatic expertise, but also to small to medium-sized brands looking to navigate this complex and often confusing new world.</p> <p style="font-weight: normal;">With IBMs Watson, Salesforce's Einstein and Amazon's Alexa, I'm left wondering if the soothing voice of AOL's Connie will return for the programmatic industry. "You've got a new customer", perhaps? </p> <h3>Rise of peer-to-peer data sharing (programmatic 3.0)</h3> <p><strong>Chris O'Hara:</strong></p> <p>The story of programmatic can be summed up as battle for control over the user, and the gateways for audience access.</p> <p>In its first iteration, programmatic meant finding users on exchanges using real-time bidding.</p> <p>It was a difficult and manual process to “whitelist” preferred sites, and impossible to control reach into specific audiences, due to the inherent nature of bidding (you might not win enough bids to get scale). </p> <p>Then, we saw the first green shoots of “programmatic direct” in which premium marketplaces tied to media planning platforms sprung up (iSocket and ShinyAds), where publishers could set their own price for premium inventory and make direct deals with buyers.</p> <p>Those platforms never found scale, mostly due to the lack of dynamic inventory management, and the fact that buyers did not want to embrace another buying technology.</p> <p>The real programmatic 2.0 model started with the introduction of private marketplaces and Deal ID. This was a great way to leverage an efficient <a href="https://econsultancy.com/blog/65677-a-super-accessible-beginner-s-guide-to-programmatic-buying-and-rtb/">RTB</a> buying methodology with some restrictions, and limit access to preferred inventory.</p> <p>We have seen this model further evolve into header bidding technology, which is basically a smarter waterfall approach for publishers. </p> <p>These innovations helped publishers get more for their premium inventory, and marketers can leverage programmatic tech to get more precision reach, with more granular controls over inventory.</p> <p>However, these approaches were built on top of an existing ecosystem that was built to shrink the number of working media dollars and distribute them to technology providers, before money ended up in the publisher’s pocket.</p> <p>Marketers still find a $10 spend reduced to $2 in effective media, after the “ad tech tax” is extracted by trading desks, DSPs, 3rd party data costs, SSPs, and private marketplace fees. Unsustainable, to say the least. </p> <p>What we are seeing now, however, is the rise of a dramatic new approach to data driven marketing that gives the data buyer and owner more control.</p> <p>Marketers have increasingly turned to <a href="https://econsultancy.com/blog/67583-what-does-the-future-hold-for-data-management-platforms/">DMPs</a> to manage their inventory, and publishers are leveraging their DMP’s trust infrastructure to manage exactly which data they can make available to customers—and for very specific use cases.</p> <p>A marketer and publisher on the same DMP infrastructure can choose to “open the pipes” between their instances and share user data for specific campaigns, and start to leverage their audience targeting capabilities on more premium inventory, where people are more engaged.</p> <p>This type of peer-to-peer data sharing is happening today, and we will see not only marketers buying data from premium publishers within DMPs—but also the beginning of peer-to-peer data sharing among marketers.</p> <p>Imagine if a group of CPG marketers pooled their shopping data for non-competitive products. Or, we might see a car rental company start to share business traveler data with its preferred airline. </p> <h3>The programmatic halo effect </h3> <p><strong>Tom Wright, Head of Programmatic, Tomorrow TTH:</strong></p> <p>In an ever increasing programmatic landscape, fluid and responsive media trading has become a necessity not an option.</p> <p>With the acceptance that programmatic media buying is having an incredible impact on multi-channel conversions, now is the time for brands to implement fluid media budget strategies.</p> <p>Programmatic display has grown from being a channel auctioning off unsold display impressions, to being a sophisticated and integral part of the overall marketing mix.</p> <p>As it exists now, buying media programmatically, creates a framework allowing the delivery of data driven, multi media content to audiences via all connected devices, at scale.</p> <p>I believe 2017 will see programmatic media buying cement itself as an infrastructure that paves the way for traditional channels, such as TV, to move into a programmatic format capable of learning, optimising and reacting, considerate of data made available from other programmatic enabled formats.</p> <p>It is this potential for symbiosis which requires a commitment to real fluidity of advertising budget, at scale, in real time between channel, format and device.</p> <p>It will be the responsibility of the 2017 marketer to be brave enough to move away from treating programmatic display in isolation, and start considering the halo effect that the scale and impact of this channel has upon the overall performance of all other paid media channels in the same way TV, Outdoor or print does.</p> <p>This blended approach is something we're championing with our clients and the uplift in performance has been dramatic.</p> <p>Combined with enhancements in attribution technology, it will come down to the orchestration of quantitative evidence and qualitative reasoning to unlock the true power of programmatic media buying, but it will always be about a balance between media trader and the technology at their disposal. </p> tag:econsultancy.com,2008:BlogPost/68639 2016-12-15T10:02:00+00:00 2016-12-15T10:02:00+00:00 How CRM and a DMP can combine to give a 360-degree view of the customer Chris O'Hara <p>Of course, there is a clearer dividing line between marketing tech and ad tech: personally identifiable information, or PII. Marketers today have two different types of data, from different places, with different rules dictating how it can be used.</p> <p>In some ways, it has been natural for these two marketing disciplines to be separated, and some vendors have made a solid business from the work necessary to bridge PII data with web identifiers so people can be “onboarded” into cookies.</p> <p>After all, marketers are interested in people, from the very top of the funnel when they visit a website as an anonymous visitor, all the way down the bottom of the funnel, after they are registered as a customer and we want to make them a brand advocate.</p> <p>It would be great — magic even — if we could accurately understand our customers all the way through their various journeys (the fabled “360-degree view” of the customer) and give them the right message, at the right place and time. The combination of a strong CRM system and <a href="https://econsultancy.com/blog/67583-what-does-the-future-hold-for-data-management-platforms/">an enterprise data management platform (DMP)</a> brings these two worlds together.</p> <p>Much of this work is happening today, but it’s challenging with lots of ID matching, onboarding, and trying to connect systems that don’t ordinarily talk to one another. However, when <a href="https://econsultancy.com/blog/64545-what-is-crm-and-why-do-you-need-it/">CRM</a> and DMP truly come together, it works.</p> <p>What are some use cases?</p> <h3>Targeting people who haven’t opened an email</h3> <p>You might be one of those people who don’t open or engage with every promotional email in your inbox, or uses a smart filter to capture all of the marketing messages you receive every month.</p> <p>To an email marketer, these people represent a big chunk of their database. Email is without a doubt the one of the most effective digital marketing channels, even though as few as 5% of people who engage are active buyers. It’s also relatively fairly straightforward way to predict return on advertising spend, based on historical open and conversion rates.</p> <p>The connection between CRM and DMP enables the marketer to reach the 95% of their database everywhere else on the web, by connecting that (anonymized) email ID to the larger digital ecosystem: places like Facebook, Google, Twitter, advertising exchanges, and even premium publishers.</p> <p><em>Facebook's custom audiences uses email addresses to target ads</em></p> <p><img src="https://assets.econsultancy.com/images/0008/2423/Facebook_custom_audiences.png" alt="" width="800" height="359"></p> <p>Understanding where the non-engaged email users are spending their time on the web, what they like, their behavior, income and buying habits is all now possible. The marketer has the “known” view of this customer from their CRM, but can also utilise vast sets of data to enrich their profile, and better engage them across the web.</p> <h3>Combining commerce and service data for journeys and sequencing</h3> <p>When we think of the customer journey, it gets complicated quickly. A typical ad campaign may feature thousands of websites, multiple creatives, different channels, a variety of different ad sizes and placements, delivery at different times of day and more.</p> <p>When you map these variables against a few dozen audience segments, the combinatorial values get into numbers with a lot of zeros on the end. In other words, the typical campaign may have hundreds of millions of activities — and tens of millions of different ways a customer goes from an initial brand exposure all the way through to a purchase and the becoming a brand advocate.<br> </p> <h3>How can you automatically discover the top 10 performing journeys?</h3> <p>Understanding which channels go together, and which sequences work best, can add up to tremendous lift for marketers.</p> <p>For example, a media and entertainment company promoting a new show recently discovered that doing display advertising all week and then targeting the same people with a mobile “watch it tonight” message on the night of it aired produced a 20% lift in tune-in compared to display alone. Channel mix and sequencing work.</p> <p>And that’s just the tip of the iceberg — we are only talking about web data.</p> <p>What if you could look at a customer journey and find out that the call-to-action message resonated 20% higher one week after a purchase?</p> <p>A pizza chain that tracks orders in its CRM system can start to understand the cadence of delivery (e.g. Thursday night is “pizza night” for the Johnson family) and map its display efforts to the right delivery frequency, ensuring the Johnsons receive targeted ads during the week, and a mobile coupon offer on Thursday afternoon, when it’s time to order.</p> <p><img src="https://assets.econsultancy.com/images/0008/2425/pizza.jpg" alt="" width="724" height="483"></p> <p>How about a customer that has called and complained about a missed delivery, or a bad product experience? It’s probably a terrible idea to try and deliver a new product message when they have an outstanding customer ticket open. Those people can be suppressed from active campaigns, freeing up funds for attracting net new customers.</p> <p>There are a lot of obvious use cases that come to mind when CRM data and web behavioral data is aligned at the people level. It’s simple stuff, but it works.</p> <p>As marketers, we find ourselves seeking more and more precise targeting but, half the time, knowing when not to send a message is the more effective action.</p> <p>As we start to see more seamless connections between CRM (existing customers) and DMPs (potential new customers), we imagine a world in which <a href="https://econsultancy.com/reports/marketing-in-the-age-of-artificial-intelligence/">artificial intelligence</a> can manage the cadence and sequence of messages based on all of the data — not just a subset of cookies, or email open rate.</p> <p>As the organizational and technological barriers between CRM and DMP break down, we are seeing the next phase of what Gartner <a href="http://www.gartner.com/it-glossary/digital-marketing-hub/">says</a> is the “marketing hub” of interconnected systems or “stacks” where all of the different signals from current and potential customers come together to provide that 360-degree customer view.</p> <p>It’s a great time to be a data-driven marketer!</p> <p>Chris O’Hara is the head of global marketing for Krux, the Salesforce data management platform.</p> <p><em>For more on this topic, see:</em></p> <ul> <li><a href="https://econsultancy.com/reports/the-role-of-crm-in-data-driven-marketing/"><em>The Role of CRM in Data-Driven Marketing</em></a></li> <li><a href="https://econsultancy.com/blog/68408-the-five-fundamentals-of-data-driven-marketing/"><em>The five fundamentals of data-driven marketing</em></a></li> <li><a href="https://econsultancy.com/training/courses/big-data-driven-marketing-how-to-get-it-right/"><em>Econsultancy’s range of Data-Driven Marketing Training Courses</em></a></li> </ul> tag:econsultancy.com,2008:BlogPost/68628 2016-12-14T14:11:58+00:00 2016-12-14T14:11:58+00:00 Amazon could become an ad tech force in 2017 Patricio Robles <p>As detailed last week by the Wall Street Journal, Amazon's first two products launched under the APS umbrella, Transparent Ad Marketplace and Shopping Insights Service, are potential game-changers for the company and signal that Amazon could be ready to make a big ad tech splash.</p> <h3>Shopping Insights Service</h3> <p>Amazon has perhaps the most deep, and therefore valuable, customer database in retail, and its Shopping Insights Service enables publishers to tap into that. Through the service, publishers can gain insight into their audiences based on Amazon's shopping data. </p> <p>Shopping Insights Service has been tested by a number of publishers, including Time Inc., which discovered using Amazon's new service that its Real Simple website is popular with new moms who are interested in purchasing baby products. The media company says that it will be able to use this data to lure advertisers. </p> <p>Amazon's new service shouldn't be a hard sell for publishers. While other companies, like Google and Facebook, offer tools that companies can use to gain insights into their audiences, neither Google nor Facebook has the kind of shopping data Amazon has, so it's likely that publishers will be eager to use Shopping Insights Service.</p> <h3>Transparent Ad Marketplace</h3> <p>The second product under the APS umbrella, Transparent Ad Marketplace, is a cloud-based header bidding solution. Interest in and adoption of <a href="http://digiday.com/publishers/wtf-header-bidding/">header bidding</a> has exploded in the past year thanks to publisher (and <a href="https://econsultancy.com/blog/68460-are-retailers-compromising-site-performance-in-pursuit-of-ad-dollars/">even retailer</a>) motivation to maximize ad revenue.</p> <p>But header bidding, which enables publishers to conduct simultaneous bidding for ad inventory across multiple providers, has also proven to be problematic. The most common header bidding solutions are implemented on the client side, which can impact page performance negatively.</p> <p>Amazon's Transparent Ad Marketplace aims to alleviate that problem. As Amazon VP of Worldwide Advertising Platforms, Tim Craycroft, <a href="http://www.wsj.com/articles/amazon-wants-to-help-publishers-make-more-money-from-ads-1481138120">explained</a> to the Wall Street Journal, Amazon's header bidding technology operates in the company's cloud, not on the client-side.</p> <p>"That should let publishers pull in multiple sources of demand without clogging up their websites with lots of code from different header bidding providers, and slowing down their page loads," he said.</p> <p>In addition to addressing performance concerns that have been a thorn in the side of today's most common header bidding implementations, there is also the potential for Amazon to apply its shopping data to the header bidding process to the benefit of both publishers and advertisers, something that could make Transparent Ad Marketplace particularly attractive.</p> <h3>Amazon's advantages</h3> <p>Amazon's advantages for making a big ad tech splash aren't limited to its data. Observers note that Amazon's ownership of AWS, its cloud computing platform service, offers it access to lots of computing power, something that is necessary for the kind of data crunching that drives the increasingly programmatically-driven digital advertising economy.</p> <p>And Amazon's access to that computing power comes at perhaps a lower cost than any other company.</p> <p>That might explain why Amazon will reportedly not charge publishers for access to Shopping Insights Service or Transparent Ad Marketplace, although the company says it might offer paid features and products in the future.</p> <h3>Success is not guaranteed</h3> <p>Despite its advantages, Amazon's success as a major ad tech player isn't guaranteed. For instance, its cloud-based Transparent Ad Marketplace is attractive on paper, but its viability will likely depend on Amazon's ability to forge relationships and build integrations with header bidders. </p> <p>Google, which is threatened by header bidding, is working on its own header bidding solution. If it can appease publishers with that, Google could disrupt the header bidding market that exists today and make it harder for Amazon to compete with its offering.</p> <p>But Amazon's ad tech success might depend less on tech than the current politics of the ad industry. Publishers and advertisers alike are increasingly concerned about the dominance of Facebook and Google, and while they might be wary of a giant company like Amazon, it's possible the market will decide that a Big 3 is better than a Big 2.</p> tag:econsultancy.com,2008:BlogPost/68626 2016-12-13T14:09:30+00:00 2016-12-13T14:09:30+00:00 Three reasons to appreciate Spotify’s latest data-driven ad campaign Nikki Gilliland <p>Here’s three reasons why it works.</p> <h3>Real-time and relatable elements</h3> <p>Due to roll out in 14 different markets, Spotify’s campaign is designed to draw a line under the strange beast that was 2016, and it does so by showcasing the listening activity of its users on outdoor billboards.</p> <p>Naturally, it also takes the opportunity to draw on the various events that dumbfounded us all throughout the year.</p> <p>For example, one billboard in the UK says: “Dear 3,749 people who streamed ‘It's The End Of The World As We Know It’ the day of the Brexit Vote. Hang in There”.</p> <p><img src="https://assets.econsultancy.com/images/0008/2312/Spotify_1.JPG" alt="" width="750" height="487"></p> <p>As well as using humour to poke fun at its own audience, it’s also a rather wry take on what was an extremely eventful year. </p> <p>By talking about large topics, like global events, as well as the personal and every day, such as the music we listen to, the campaign comes off as both relevant and relatable.</p> <p>The timing is pretty smart, too. Unlike most Christmas campaigns, which tend to use sentimental and syrupy themes, Spotify is going against the grain with its light-hearted and sarcastic tone here.</p> <p>With HotelTonight also creating a similarly funny holiday campaign – there’s obviously a trend for going against tradition this year.</p> <h3>Hyper-localised</h3> <p>As well as talking about global and political events, the campaign is also super personal. </p> <p>It draws on data to pick out the (often questionable) music listening habits of its users, with tongue-in-cheek commentary for added humour.</p> <p>A personal favourite is the Justin Bieber-inspired billboard that says: “Dear person who played ‘Sorry’ 42 times on Valentine’s Day, what did you do?”</p> <p>Other billboards are incredibly localised, mentioning the listening behaviour of local residents, such as: "Dear person in the Theater District who listened to the Hamilton soundtrack 5,376 times this year. Can you get us tickets?"</p> <p>By referencing the surrounding area, it is also effective for targeting and creating a deeper connection with a key demographic.</p> <h3>Creates a memorable moment</h3> <p>The CMO of Spotify, Seth Farban, recently spoke about the debate over big data and how it could potentially be muting creativity in marketing.</p> <p>In contrast to this suggestion, he says: “For us, data inspires and gives an insight into the emotion that people are expressing.”</p> <p>I think this is why the campaign works so well.</p> <p>Spotify is a company that relies on data to give its users a better experience. Let’s say a fashion brand or ecommerce company advertised what customers bought and when – it could come across as creepy or even off-putting.</p> <p>So why is it different for Spotify? Like Farban says, it’s because the brand is wrapped up in the emotion of music.</p> <p>Likewise, it is also expected. Users understand Spotify has access to listener data, using it to dictate the platform’s algorithm and personalisation features. This makes it feel less intrusive. </p> <p>Finally, going back to the relatable element – advertising our ‘guilty pleasures’ or songs we might feel embarrassed listening to makes the intent appear jovial and harmless in nature.</p> <p><img src="https://assets.econsultancy.com/images/0008/2313/Spotify_3.JPG" alt="" width="750" height="498"></p> <h3>In conclusion…</h3> <p>Spotify’s campaign is clever in how it uses its own customer-base as a marketing asset.</p> <p>Building on the platform’s reputation for giving users a curated and personal experience, it uses humour to shine a light on the ‘weird’ but wonderful ways we related to the brand in 2016.</p> <p><strong><em>Related articles:</em></strong></p> <ul> <li><em><a href="https://econsultancy.com/blog/66344-spotify-unveils-new-playlist-based-ad-targeting/" target="_blank">Spotify unveils new playlist-based ad targeting</a></em></li> <li><em><a href="https://econsultancy.com/blog/68522-the-impact-of-technology-and-social-media-on-the-music-industry/" target="_blank">The impact of technology and social media on the music industry</a></em></li> </ul>