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Multichannel attribution 2017_04

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Basil Boluk
Basil Boluk

This document discusses the importance of multichannel attribution for marketers. It notes that consumers are increasingly device-agnostic and pick the most convenient channel. While many companies have basic digital attribution models, advanced multichannel attribution is needed to understand what marketing activities drive consumer actions. The document provides an overview of attribution and discusses how marketers are focusing more on cross-channel measurement and viewthrough conversions as part of multichannel attribution. However, cross-device attribution remains a major challenge for many marketers.

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April 2017 Today, consumers are convenience-driven, which often means device-agnostic. They’re picking the channel that’s the most convenient, whether that’s looking down at their mobile phone or ahead at the store shelf. For marketers wanting to effectively tie consumer behavior to specific campaign activities, this is where multichannel attribution comes in. eMarketer has curated this Roundup of articles, insights and interviews to help you understand how crucial multichannel attribution is for marketers now more than ever. MULTICHANNEL ATTRIBUTION ROUNDUP presented by
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 2 MULTICHANNEL ATTRIBUTION ROUNDUP Overview Attribution is crucial for US companies to track the impact of their marketing efforts. Although the majority have some type of digital attribution model in place, the need for more advanced multichannel attribution is important so marketers can determine which components of their marketing program led to a consumer’s specific action. Attribution—which is a method of assigning credit to a particular marketing-driven interaction or other brand- related touchpoint—is important to marketers to help inform their media planning and buying decisions. Overall, the majority (81%) of US companies with at least 100 employees using more than one digital channel for their marketing campaign have an attribution model in place this year, according to eMarketer estimates. Yet, as the number of digital channels, platforms and ad formats continue to grow, it’s critical that marketers sink their teeth into more advanced, or multichannel attribution models. This way, they can pin down which channels are in fact driving ad performance. Take a look at just how fragmented consumers’ time is being spent across all media. According to eMarketer estimates, while US adults spend just over 4 hours a day watching TV, they’re also consuming upwards of another nearly 6 hours on digital. Break that down further, and the numbers show that adults are investing 3 hours on mobile (nonvoice) and another 2 on desktop/laptop. While multichannel attribution models had not been widely used in the past, eMarketer numbers suggest adoption is growing. This year, 50.2% of US companies that are using more than one digital marketing channel currently use multichannel attribution models. By 2018, eMarketer predicts that 58.5% will use a multichannel attribution model for tracking their digital marketing efforts.. % of total Share of US Companies Using Digital Attribution Models, 2014-2018 2014 61% 2015 68% 2016 75% 2017 81% 2018 86% Note: companies with 100+ employees that use more than one digital marketing channel; an attribution model is a way to differentiate the respective contributions of various marketing channels to a desired outcome; includes first- and last-touchpoint models and more complex multichannel models Source: eMarketer, Oct 2016 217117 www.eMarketer.com Total per day=12 hours 7 minutes Digital hrs:mins Average Time Spent per Day with Major Media by US Adults, 2017 Note: ages 18+; time spent with each medium includes all time spent with that medium, regardless of multitasking; for example, 1 hour of multitasking on desktop/laptop while watching TV is counted as 1 hour for TV and 1 hour for desktop/laptop; *excludes digital; **includes all internet activities on desktop and laptop computers Source: eMarketer, April 2017 225407 www.eMarketer.com Digital 5:50 TV* 4:04 Radio* 1:26 Print* 0:25 Other* 0:21 Mobile (nonvoice) 3:14 Desktop/ laptop** 2:08 Other connected devices 0:28
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 3 Marketers Renew Interest in Cross-Channel Attribution But focus on programmatic buying for mature formats slips When it comes to collecting and evaluating audience data, marketers can choose from a multitude of tactics. Recent research suggests there’s an increased interest in cross-channel measurement and attribution this year, edging ahead of former go-to tactics like general audience analytics and programmatic media buying. Almost 60% of US digital marketing and media practitioners polled in January 2017 by the Interactive Advertising Bureau (IAB) and Winterberry Group said they expect to be engaged in cross-channel measurement and attribution this year. But there is a caveat: When IAB and Winterberry conducted this same survey back in January 2016, a little over a half of marketers said they expected to spend more time with cross-channel measurement and attribution. Yet, according to the recent data, only a third of those polled actually engaged more effort on cross-channel measurement and attribution in 2016. For 2017, marketers have predicted similarly, so it isn’t clear that time spent on cross-channel analysis will actually grow in line with marketers’ proposed intentions. It apparently didn’t last year. That aside, there’s certainly interest in the tactic and it’s justified. Attribution is key for marketers looking to optimize media channels in this increasingly fragmented world. “Attribution is key for marketers looking to optimize media channels in this increasingly fragmented world.” For instance, the retail industry is taking a more serious stance on cross-channel marketing by incorporating both online and offline tactics, and gaining greater insight into their customer base. About four in 10 retail marketers worldwide said they will implement cross-channel attribution initiatives in 2017, according to a Yes Lifecycle Marketing survey. While doubling down on cross-channel attribution, the IAB/Winterberry Group survey found there were some tactics that respondents said they’d be spending less energy on. These included general audience analytics, programmatic media buying for more mature markets and predictive modeling. The decreasing interest in programmatic for established formats is particularly interesting, considering recent news about advertisers boycotting Google over objectionable content near ads. Apparently, marketers want to take a more hands-on approach in deciding where their ads appear and don’t appear. % of respondents Tactics that Occupied vs. Will Occupy Their Time/ Resources According to US Digital Marketing/Media Practitioners, 2015-2017 Cross-channel measurement and attribution Programmatic media buying for established formats Cross-channel audience identification/matching Advertising content/experience optimization General audience analytics Predictive modeling or segmentation Programmatic media buying for emerging formats Yield optimization Online retargeting Online-to-offline (or offline-to- online) retargeting Site content/experience optimization Single-channel measurement and attribution Occupied in 2015 35.4% 50.5% 45.5% 27.3% 47.5% 44.4% 37.4% 32.3% 34.3% 14.1% 25.3% 25.3% Occupied in 2016 33.3% 48.8% 33.3% 26.2% 52.4% 45.2% 29.8% 28.6% 33.3% 25.0% 21.4% 25.0% Will occupy in 2017 57.1% 47.6% 42.9% 40.5% 40.5% 38.1% 38.1% 33.3% 22.6% 22.6% 22.1% - Note: respondents selected up to 5 Source: Interactive Advertising Bureau (IAB) and Winterberry Group, "The Outlook for Data 2017: A Snapshot Into the Evolving Role of Audience Insight," Jan 30, 2017 222736 www.eMarketer.com
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 4 Marketers Turn to Cross-Device Targeting to Better Understand Their Audience Cross-device analysis is broadening beyond simply IDing individuals Over the past 12 months, advertisers’ understanding of cross-device targeting and the identity matching methodologies behind the technology have improved. With that improvement comes added expectations for the types of data that can be added to these identity graphs and the locations in which that targeting can be applied, such as in living rooms and in stores. Demand for cross-device targeting is high, and there is no shortage of ad tech players and solutions providers that have made headlines in the past year boasting such offerings. But advertisers are still incorporating these capabilities into their marketing programs. Among the marketers in North America polled by Econsultancy in a September 2016-released survey, less than half reported the ability to understand cross-device behavior, understand cross-channel purchase paths and tailor creative to meet those understood behaviors. Slightly more than half reported the ability to utilize customer data to find similar audiences, but it’s important to acknowledge that such a capability might be applied to a single platform or channel, not a cross-device or cross-channel strategy. “Ironically, there are probably more companies that are targeting media across devices than there are companies that actually understand the cross-device behavior of their customer base,” said Brandon Wishnow, executive director of measurement and activation for Ovative/ group, a media consulting firm that specializes in helping clients with managing their audience data in order to carry out essential digital functions, such as omnichannel measurement. “They’re using any number of targeting technologies that are out there to buy media, but they’re not necessarily close-looped with their measurement.” Such a distinction is becoming more important. Cross- device may have started as a solution for identifying individuals across multiple devices and screens, but it is broadening into something buyers and sellers turn to for a much more complete understanding of their audiences. “In the last year or so, marketers have begun to realize that it’s not just cross-device targeting and measurement,” said Tomer Naveh, chief technology officer at Adgorithms, an artificial intelligence marketing firm. “It’s cross-device and cross-channel to look at the holistic journey that the users go through to understand how to optimize those journeys.” “It’s cross-device and cross-channel [that’s needed] to look at the holistic journey that the users go through to understand how to optimize those journeys,” said Adgorithms CTO Naveh. As a result, buyers, sellers and other tech players requiring audience identification capabilities are moving quickly to change how they vet cross-device solution providers. % of respondents Consumer-Related Capabilities at Their Company According to Marketers in North America, March 2016 Use data about our customers to find similar audiences 58% Understand our customers' typical cross-channel buying journeys 48% Deliver dynamic content across digital formats, such as display, mobile and video advertising, in response to individual's behavior 46% Understand our customers' cross-device behaviors 39% Note: n=212 Source: Econsultancy, "Customer Recognition: How Marketing is Failing at its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016 216902 www.eMarketer.com
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 5 Viewthroughs Gain Attention as Attribution Tactic Platforms such as Snapchat, Instagram aren’t oriented around a click Click-based attribution models have long been a staple of digital advertising. These legacy models have endured despite mounting research against their validity, thanks to issues associated with click fraud and because so few conversions are influenced by a single channel or touchpoint. Many marketers are keen to turn to blended attribution models that take clicks and viewthroughs into account. New data shows that times are changing. A recent survey of marketing professionals in the US and Europe conducted by Qualtrics for AdRoll found that although 65% of respondents said they use single-click attribution, 57% plan on changing their model. The reason? Consumer engagement on platforms that marketers increasingly rely on to drive conversions are not necessarily click-based anymore. “Just a few years ago, we were in a search-dominated market,” said Shane Murphy, vice president of marketing at AdRoll. “If consumers wanted to buy something, they would search for a product, see some search ads, click on them and convert. In that world, a click-based model makes sense.” But the prevalence of visual social platforms such as Instagram and Snapchat have changed the way consumers shop. “These new platforms aren’t oriented around a click,” Murphy said. “Instagram, for example, is all about building a brand and targeting people across multiple different platforms in order to drive conversion. Given how much the customer journey has changed, marketers can’t just measure clicks anymore.” As the survey suggests, this has many keen to turn to blended attribution models, which the firm defines as models that take clicks and viewthroughs into account. Thanks to that growing recognition, marketers appear to be placing greater emphasis on conversions generated by viewthroughs, or instances when consumers see ads but don’t actually click on them. Findings from the same survey examined a three-year period, finding that the importance or weight assigned to viewthrough conversions has increased over that timeframe. In 2014, only 14% of marketers polled in the US and Europe assigned 50% or more conversion influence to viewthroughs. But in 2016, nearly half (46%) of respondents said they attributed at least 50% of the weight to viewthrough conversions. Overall, only 1% of respondents said they didn’t count viewthrough conversions at all in 2016, down from 8% in 2014. Across the broader industry, others are also looking to enhance their viewthrough capabilities. Google, for example, announced recently that it will decrease the viewthrough conversion window in its AdWords tool from 30 days to one day, because ads are more likely to drive a purchase on the day they’re seen. For marketers using Google AdWords to measure ad effectiveness, that means that only sales that take place within 24 hours of an ad view will be counted as a conversion. % of respondents Weight that Marketing Professionals in Europe and the US Assign to Viewthrough Conversions, 2014-2016 2014 7% 38% 33% 14% 8% 0%-9% 10%-24% 25%-49% 50%-100% Don't count viewthrough conversions Note: read as 6% of respondents attribute <10% of conversions to view- through action in 2016; numbers may not add up to 100% due to rounding Source: AdRoll, "2017 State of Performance Marketing" conducted by Qualtrics, March 7, 2017 224207 www.eMarketer.com 2015 5% 19% 45% 29% 2% 2016 6% 17% 29% 46% 1%
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 6 Cross-Device Attribution is Crucial, But Challenging for Marketers Nearly three-quarters say matching customers across multiple devices is a priority Understanding consumers’ behavior as they switch between devices remains one of the toughest challenges facing marketers today. According to recent research investigating marketers’ digital capabilities, the problem doesn’t seem to be getting any easier. In a September 2016-released survey by Econsultancy investigating the gaps between digital priorities and capabilities at companies in North America, “matching customers across multiple devices” was mentioned as a digital priority by nearly three-quarters of the marketers polled. Yet only 14% of marketers in the same survey said their company had the capability to handle such matching, a gap of 60 percentage points. Even though cross-device attribution did not have the biggest gap between company priorities and capabilities, additional data from Econsultancy emphasizes the challenge that the tactic poses for many organizations. When asking the same group of executives about the consumer-related capabilities of their companies, only 39% said they were able to understand their customers’ cross- device behaviors, lower than any other capability mentioned. % of respondents Digital Priorities vs. Capabilities at Their Company According to Marketers in North America, March 2016 Associating conversion events with marketing 84% 10% Tailoring messaging by channel 76% 13% Understanding customer behavior over time 75% 12% Matching customers across multiple devices 74% 14% Priority Capability Note: n=184 Source: Econsultancy, "Customer Recognition: How Marketing is Failing at its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016 216903 www.eMarketer.com % of respondents Consumer-Related Capabilities at Their Company According to Marketers in North America, March 2016 Use data about our customers to find similar audiences 58% Understand our customers' typical cross-channel buying journeys 48% Deliver dynamic content across digital formats, such as display, mobile and video advertising, in response to individual's behavior 46% Understand our customers' cross-device behaviors 39% Note: n=212 Source: Econsultancy, "Customer Recognition: How Marketing is Failing at its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016 216902 www.eMarketer.com
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 7 The Advantages of Marketing Mix Models Matt Krepsik Global Head of ROI Nielsen Most marketers rely on either marketing mix models or a form of attribution modeling to measure how effectively their marketing efforts are driving sales. There are pros and cons to both approaches, especially as both continue to mature, but marketing mix models take some elements into account that attribution models often do not. Matt Krepsik, global head of ROI at Nielsen, spoke with eMarketer’s Maria Minsker about making the case for marketing mix models and how brands can benefit from them. eMarketer: A growing number of vendors are offering marketing mix models for measuring the impact of marketing tactics on sales. Can you explain how these models work? Matt Krepsik: Marketing models enable companies to understand and assess the incremental value of their investments. What makes marketing mix models unique is their capability to take effective frequency and reach into account. For example, the models can identify that if a brand is launching a TV campaign, it needs to drive a reach of around 60% of viewers. That percentage is identified as a saturation point, and after it’s reached the brand will start to see diminishing returns. On top of that, there’s the concept of effective frequency, which is the number of times a company should invest in order for a customer to see an ad and respond to it. The embedded intelligence behind marketing mix model decisioning is based on an understanding of reach and frequency, which enables marketers to make better decisions and optimize their expense. eMarketer: How effective are these models at predicting how marketing drives sales? Krepsik: When the models control other factors that influence businesses, they produce a fairly strong level of accuracy. Our Benchmark Media Optimizer tool uses a marketing mix model, for example, and we typically make predictions within 5% to 6% of the actual in- market performance. eMarketer: In what ways can marketers take the insight they gain from marketing mix models and make it actionable? Krepsik: Let’s say I’m a brand owner and I’m trying to figure out what my media plan will look like next year. Perhaps I want to shift dollars to a digital campaign. What’s amazing is a marketing mix model not only allows marketers to make those budgetary decisions with really solid intelligence, but can also push those decisions forward into other activation platforms, such as the marketing cloud. eMarketer: What happens when a brand uses a marketing mix model from one vendor, but relies on a different marketing cloud provider? Do integration challenges arise? Krepsik: No brand owner in the world is going to use the same tool for everything. [That’s why it’s important to] build direct integrations to the buying platforms of choice, whether those are agency platforms or third-party platforms, such as the Adobe Marketing Cloud. eMarketer: What’s the next phase for marketing mix models? Are they going to become smarter and more accurate over time? Krepsik: We already know so much about how brand owners make investments in their media buys that artificial intelligence [AI] is the next phase. An AI prediction engine will be able to make two or three recommendations on media buys before even building a model. Rather, the prediction will be based on a brand’s profile and what is generally known about consumers in a specific category and in a specific country.
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 8 Still Targeting Devices Rather than Users? Why that Is Problematic for Programmatic Marc Grabowski Executive Vice President, Global Supply and Business Development Criteo Marc Grabowski, executive vice president of global supply and business development at ad retargeting firm Criteo, spoke with eMarketer’s Lauren Fisher about the importance of taking a user-centric view when buying programmatically and shared his observations on the latest trends in header bidding. eMarketer: What are some of the big trends you are seeing unfold in the programmatic space today? Marc Grabowski: We’re seeing a number of things, but the first is mobile cross-device or omnichannel. We’ve obviously been seeing this area unfold for years, with revenues and purchase behavior moving over from desktop to mobile and tablets. We are continuing to see that in 2017. Criteo works with a lot of ecommerce and retail, and we’ve seen that the number of conversions taking place on smartphones is up enormously year over year. In our latest study, “The State of Cross-Device Commerce,” we found it’s up 41%, so a big number. That probably doesn’t come as a big surprise, but we are also seeing that the customer journey is longer and involves more devices than a lot of people previously suspected. “The customer journey is longer and involves more devices than a lot of people previously suspected.” A lot of people still look at things in terms of device view vs. user view. Device view is if you look at how people are interacting with the brand on a single device. User view is if you look at the user across all devices. We found that if you look at a device-centric view, about 43% of transactions take place in the first visit to a website. But if you look at a user-centric view, you see that it’s only 32% on the first visit. That means that, looking at a user across multiple devices along their journey, they have a much longer path to purchase than [if you look] at the user on just a single device. So it’s important for us to examine the value of that user and attribute that properly across those devices, because it then allows us to bid more for those users and find them in much more valuable areas than if we just took a single device view. eMarketer: Does moving from a device-level view to a user-level view substantially change your bid strategy? It seems like it would, given the numbers you shared above. Grabowski: In programmatic, it makes a big difference. We can bid more for that user because we can assure a higher value to an advertiser longer-term, because we know more about their user behavior. If we’re only attributing sales to a user on a single device, the challenge is we’re attributing too low. Instead of assessing a bid based on the likelihood for a user to convert on a particular device, we need to assess a bid based on the likelihood of that user to convert, period. If we look at a device-centric view of conversions in the US, we see about a 6% conversion rate. But if we look at a user- centric view, we see [that rate] go up to about 9%. That allows us to bid 1.4 times higher, and allows the advertiser to capture more value for that user when they’re bidding than if they were just looking at a single device. eMarketer: I know Criteo is very active in the header bidding arena today. What big trends are you seeing? Grabowski: We are definitely seeing that header bidding is important, and it’s a big topic. There are some benefits and drawbacks for header bidding. One of the big benefits is it brings a lot of demand forward for the publisher, and it’s definitely an advantage for savvy buyers. But it
Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 9 becomes very difficult for smaller, less sophisticated buyers to evaluate inventory across platforms, which is probably going to lead to greater consolidation it the space. “If we look at a device-centric view of conversions in the US, we see about a 6% conversion rate. But if we look at a user- centric view, we see [that rate] go up to about 9%.” When people were buying in the waterfall in the past, you’d see an impression. You’d evaluate the impression. Then you’d determine if you wanted to bid or not. But now, if you’re buying across multiple [supply-side platforms] SSPs as well as publisher direct, you might see that impression come up in 10 or 15 different auctions. It becomes much more difficult for buyers to understand where they should be buying that [impression] and what they should be bidding on it. Over the past year, we’ve actually had a lot of the [demand- side platforms] DSPs coming to us and saying, “Look, it’s getting more and more difficult for us to buy across multiple SSPs. Can you help us do that? Can you do the bidding on our behalf so that we can actually end up buying some of that inventory through you?” That’s been a big trend for a lot of companies, and I think it’s going to lead to greater consolidation in the next year or two. “Publishers are trying to figure out how to do server-to-server, but they just moved over to header bidding or to a wrapper and have now realized they have to make another move.” eMarketer: Many of the conversations about consolidation have to do with the transition to server-to- server header bidding, in which the publisher chooses a primary header partner though which the auction with all other header partners will run. There’s a lot of hype around server-to-server, since it enables publishers to take the auction out of the browser—thereby improving some of the page-load latency issues header has caused. Are you seeing many publishers transitioning to server-to- server setups? Grabowski: We see a lot of publishers asking questions, but we haven’t seen a lot of publishers make that move yet. There are definitely pockets where they have, and I think that over the next six to nine months, it’s going to pick up a lot of steam. Publishers are trying to figure out how to do server-to-server, but they just moved over to header bidding or to a wrapper and have now realized they have to make another move. It does take time, and a lot of publishers don’t have the IT resources to be able to roll out new infrastructure that quickly. Now the benefit for server-to-server is less latency, as well as potentially feeling less data risk and leakage. And as more inventory moves over to mobile, server-to-server is not only going to address the latency, but it can also serve in-app much better. There’s no question a lot of the space will move there, but it hasn’t moved yet.
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Multichannel attribution 2017_04

  • 1. April 2017 Today, consumers are convenience-driven, which often means device-agnostic. They’re picking the channel that’s the most convenient, whether that’s looking down at their mobile phone or ahead at the store shelf. For marketers wanting to effectively tie consumer behavior to specific campaign activities, this is where multichannel attribution comes in. eMarketer has curated this Roundup of articles, insights and interviews to help you understand how crucial multichannel attribution is for marketers now more than ever. MULTICHANNEL ATTRIBUTION ROUNDUP presented by
  • 2. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 2 MULTICHANNEL ATTRIBUTION ROUNDUP Overview Attribution is crucial for US companies to track the impact of their marketing efforts. Although the majority have some type of digital attribution model in place, the need for more advanced multichannel attribution is important so marketers can determine which components of their marketing program led to a consumer’s specific action. Attribution—which is a method of assigning credit to a particular marketing-driven interaction or other brand- related touchpoint—is important to marketers to help inform their media planning and buying decisions. Overall, the majority (81%) of US companies with at least 100 employees using more than one digital channel for their marketing campaign have an attribution model in place this year, according to eMarketer estimates. Yet, as the number of digital channels, platforms and ad formats continue to grow, it’s critical that marketers sink their teeth into more advanced, or multichannel attribution models. This way, they can pin down which channels are in fact driving ad performance. Take a look at just how fragmented consumers’ time is being spent across all media. According to eMarketer estimates, while US adults spend just over 4 hours a day watching TV, they’re also consuming upwards of another nearly 6 hours on digital. Break that down further, and the numbers show that adults are investing 3 hours on mobile (nonvoice) and another 2 on desktop/laptop. While multichannel attribution models had not been widely used in the past, eMarketer numbers suggest adoption is growing. This year, 50.2% of US companies that are using more than one digital marketing channel currently use multichannel attribution models. By 2018, eMarketer predicts that 58.5% will use a multichannel attribution model for tracking their digital marketing efforts.. % of total Share of US Companies Using Digital Attribution Models, 2014-2018 2014 61% 2015 68% 2016 75% 2017 81% 2018 86% Note: companies with 100+ employees that use more than one digital marketing channel; an attribution model is a way to differentiate the respective contributions of various marketing channels to a desired outcome; includes first- and last-touchpoint models and more complex multichannel models Source: eMarketer, Oct 2016 217117 www.eMarketer.com Total per day=12 hours 7 minutes Digital hrs:mins Average Time Spent per Day with Major Media by US Adults, 2017 Note: ages 18+; time spent with each medium includes all time spent with that medium, regardless of multitasking; for example, 1 hour of multitasking on desktop/laptop while watching TV is counted as 1 hour for TV and 1 hour for desktop/laptop; *excludes digital; **includes all internet activities on desktop and laptop computers Source: eMarketer, April 2017 225407 www.eMarketer.com Digital 5:50 TV* 4:04 Radio* 1:26 Print* 0:25 Other* 0:21 Mobile (nonvoice) 3:14 Desktop/ laptop** 2:08 Other connected devices 0:28
  • 3. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 3 Marketers Renew Interest in Cross-Channel Attribution But focus on programmatic buying for mature formats slips When it comes to collecting and evaluating audience data, marketers can choose from a multitude of tactics. Recent research suggests there’s an increased interest in cross-channel measurement and attribution this year, edging ahead of former go-to tactics like general audience analytics and programmatic media buying. Almost 60% of US digital marketing and media practitioners polled in January 2017 by the Interactive Advertising Bureau (IAB) and Winterberry Group said they expect to be engaged in cross-channel measurement and attribution this year. But there is a caveat: When IAB and Winterberry conducted this same survey back in January 2016, a little over a half of marketers said they expected to spend more time with cross-channel measurement and attribution. Yet, according to the recent data, only a third of those polled actually engaged more effort on cross-channel measurement and attribution in 2016. For 2017, marketers have predicted similarly, so it isn’t clear that time spent on cross-channel analysis will actually grow in line with marketers’ proposed intentions. It apparently didn’t last year. That aside, there’s certainly interest in the tactic and it’s justified. Attribution is key for marketers looking to optimize media channels in this increasingly fragmented world. “Attribution is key for marketers looking to optimize media channels in this increasingly fragmented world.” For instance, the retail industry is taking a more serious stance on cross-channel marketing by incorporating both online and offline tactics, and gaining greater insight into their customer base. About four in 10 retail marketers worldwide said they will implement cross-channel attribution initiatives in 2017, according to a Yes Lifecycle Marketing survey. While doubling down on cross-channel attribution, the IAB/Winterberry Group survey found there were some tactics that respondents said they’d be spending less energy on. These included general audience analytics, programmatic media buying for more mature markets and predictive modeling. The decreasing interest in programmatic for established formats is particularly interesting, considering recent news about advertisers boycotting Google over objectionable content near ads. Apparently, marketers want to take a more hands-on approach in deciding where their ads appear and don’t appear. % of respondents Tactics that Occupied vs. Will Occupy Their Time/ Resources According to US Digital Marketing/Media Practitioners, 2015-2017 Cross-channel measurement and attribution Programmatic media buying for established formats Cross-channel audience identification/matching Advertising content/experience optimization General audience analytics Predictive modeling or segmentation Programmatic media buying for emerging formats Yield optimization Online retargeting Online-to-offline (or offline-to- online) retargeting Site content/experience optimization Single-channel measurement and attribution Occupied in 2015 35.4% 50.5% 45.5% 27.3% 47.5% 44.4% 37.4% 32.3% 34.3% 14.1% 25.3% 25.3% Occupied in 2016 33.3% 48.8% 33.3% 26.2% 52.4% 45.2% 29.8% 28.6% 33.3% 25.0% 21.4% 25.0% Will occupy in 2017 57.1% 47.6% 42.9% 40.5% 40.5% 38.1% 38.1% 33.3% 22.6% 22.6% 22.1% - Note: respondents selected up to 5 Source: Interactive Advertising Bureau (IAB) and Winterberry Group, "The Outlook for Data 2017: A Snapshot Into the Evolving Role of Audience Insight," Jan 30, 2017 222736 www.eMarketer.com
  • 4. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 4 Marketers Turn to Cross-Device Targeting to Better Understand Their Audience Cross-device analysis is broadening beyond simply IDing individuals Over the past 12 months, advertisers’ understanding of cross-device targeting and the identity matching methodologies behind the technology have improved. With that improvement comes added expectations for the types of data that can be added to these identity graphs and the locations in which that targeting can be applied, such as in living rooms and in stores. Demand for cross-device targeting is high, and there is no shortage of ad tech players and solutions providers that have made headlines in the past year boasting such offerings. But advertisers are still incorporating these capabilities into their marketing programs. Among the marketers in North America polled by Econsultancy in a September 2016-released survey, less than half reported the ability to understand cross-device behavior, understand cross-channel purchase paths and tailor creative to meet those understood behaviors. Slightly more than half reported the ability to utilize customer data to find similar audiences, but it’s important to acknowledge that such a capability might be applied to a single platform or channel, not a cross-device or cross-channel strategy. “Ironically, there are probably more companies that are targeting media across devices than there are companies that actually understand the cross-device behavior of their customer base,” said Brandon Wishnow, executive director of measurement and activation for Ovative/ group, a media consulting firm that specializes in helping clients with managing their audience data in order to carry out essential digital functions, such as omnichannel measurement. “They’re using any number of targeting technologies that are out there to buy media, but they’re not necessarily close-looped with their measurement.” Such a distinction is becoming more important. Cross- device may have started as a solution for identifying individuals across multiple devices and screens, but it is broadening into something buyers and sellers turn to for a much more complete understanding of their audiences. “In the last year or so, marketers have begun to realize that it’s not just cross-device targeting and measurement,” said Tomer Naveh, chief technology officer at Adgorithms, an artificial intelligence marketing firm. “It’s cross-device and cross-channel to look at the holistic journey that the users go through to understand how to optimize those journeys.” “It’s cross-device and cross-channel [that’s needed] to look at the holistic journey that the users go through to understand how to optimize those journeys,” said Adgorithms CTO Naveh. As a result, buyers, sellers and other tech players requiring audience identification capabilities are moving quickly to change how they vet cross-device solution providers. % of respondents Consumer-Related Capabilities at Their Company According to Marketers in North America, March 2016 Use data about our customers to find similar audiences 58% Understand our customers' typical cross-channel buying journeys 48% Deliver dynamic content across digital formats, such as display, mobile and video advertising, in response to individual's behavior 46% Understand our customers' cross-device behaviors 39% Note: n=212 Source: Econsultancy, "Customer Recognition: How Marketing is Failing at its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016 216902 www.eMarketer.com
  • 5. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 5 Viewthroughs Gain Attention as Attribution Tactic Platforms such as Snapchat, Instagram aren’t oriented around a click Click-based attribution models have long been a staple of digital advertising. These legacy models have endured despite mounting research against their validity, thanks to issues associated with click fraud and because so few conversions are influenced by a single channel or touchpoint. Many marketers are keen to turn to blended attribution models that take clicks and viewthroughs into account. New data shows that times are changing. A recent survey of marketing professionals in the US and Europe conducted by Qualtrics for AdRoll found that although 65% of respondents said they use single-click attribution, 57% plan on changing their model. The reason? Consumer engagement on platforms that marketers increasingly rely on to drive conversions are not necessarily click-based anymore. “Just a few years ago, we were in a search-dominated market,” said Shane Murphy, vice president of marketing at AdRoll. “If consumers wanted to buy something, they would search for a product, see some search ads, click on them and convert. In that world, a click-based model makes sense.” But the prevalence of visual social platforms such as Instagram and Snapchat have changed the way consumers shop. “These new platforms aren’t oriented around a click,” Murphy said. “Instagram, for example, is all about building a brand and targeting people across multiple different platforms in order to drive conversion. Given how much the customer journey has changed, marketers can’t just measure clicks anymore.” As the survey suggests, this has many keen to turn to blended attribution models, which the firm defines as models that take clicks and viewthroughs into account. Thanks to that growing recognition, marketers appear to be placing greater emphasis on conversions generated by viewthroughs, or instances when consumers see ads but don’t actually click on them. Findings from the same survey examined a three-year period, finding that the importance or weight assigned to viewthrough conversions has increased over that timeframe. In 2014, only 14% of marketers polled in the US and Europe assigned 50% or more conversion influence to viewthroughs. But in 2016, nearly half (46%) of respondents said they attributed at least 50% of the weight to viewthrough conversions. Overall, only 1% of respondents said they didn’t count viewthrough conversions at all in 2016, down from 8% in 2014. Across the broader industry, others are also looking to enhance their viewthrough capabilities. Google, for example, announced recently that it will decrease the viewthrough conversion window in its AdWords tool from 30 days to one day, because ads are more likely to drive a purchase on the day they’re seen. For marketers using Google AdWords to measure ad effectiveness, that means that only sales that take place within 24 hours of an ad view will be counted as a conversion. % of respondents Weight that Marketing Professionals in Europe and the US Assign to Viewthrough Conversions, 2014-2016 2014 7% 38% 33% 14% 8% 0%-9% 10%-24% 25%-49% 50%-100% Don't count viewthrough conversions Note: read as 6% of respondents attribute <10% of conversions to view- through action in 2016; numbers may not add up to 100% due to rounding Source: AdRoll, "2017 State of Performance Marketing" conducted by Qualtrics, March 7, 2017 224207 www.eMarketer.com 2015 5% 19% 45% 29% 2% 2016 6% 17% 29% 46% 1%
  • 6. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 6 Cross-Device Attribution is Crucial, But Challenging for Marketers Nearly three-quarters say matching customers across multiple devices is a priority Understanding consumers’ behavior as they switch between devices remains one of the toughest challenges facing marketers today. According to recent research investigating marketers’ digital capabilities, the problem doesn’t seem to be getting any easier. In a September 2016-released survey by Econsultancy investigating the gaps between digital priorities and capabilities at companies in North America, “matching customers across multiple devices” was mentioned as a digital priority by nearly three-quarters of the marketers polled. Yet only 14% of marketers in the same survey said their company had the capability to handle such matching, a gap of 60 percentage points. Even though cross-device attribution did not have the biggest gap between company priorities and capabilities, additional data from Econsultancy emphasizes the challenge that the tactic poses for many organizations. When asking the same group of executives about the consumer-related capabilities of their companies, only 39% said they were able to understand their customers’ cross- device behaviors, lower than any other capability mentioned. % of respondents Digital Priorities vs. Capabilities at Their Company According to Marketers in North America, March 2016 Associating conversion events with marketing 84% 10% Tailoring messaging by channel 76% 13% Understanding customer behavior over time 75% 12% Matching customers across multiple devices 74% 14% Priority Capability Note: n=184 Source: Econsultancy, "Customer Recognition: How Marketing is Failing at its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016 216903 www.eMarketer.com % of respondents Consumer-Related Capabilities at Their Company According to Marketers in North America, March 2016 Use data about our customers to find similar audiences 58% Understand our customers' typical cross-channel buying journeys 48% Deliver dynamic content across digital formats, such as display, mobile and video advertising, in response to individual's behavior 46% Understand our customers' cross-device behaviors 39% Note: n=212 Source: Econsultancy, "Customer Recognition: How Marketing is Failing at its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016 216902 www.eMarketer.com
  • 7. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 7 The Advantages of Marketing Mix Models Matt Krepsik Global Head of ROI Nielsen Most marketers rely on either marketing mix models or a form of attribution modeling to measure how effectively their marketing efforts are driving sales. There are pros and cons to both approaches, especially as both continue to mature, but marketing mix models take some elements into account that attribution models often do not. Matt Krepsik, global head of ROI at Nielsen, spoke with eMarketer’s Maria Minsker about making the case for marketing mix models and how brands can benefit from them. eMarketer: A growing number of vendors are offering marketing mix models for measuring the impact of marketing tactics on sales. Can you explain how these models work? Matt Krepsik: Marketing models enable companies to understand and assess the incremental value of their investments. What makes marketing mix models unique is their capability to take effective frequency and reach into account. For example, the models can identify that if a brand is launching a TV campaign, it needs to drive a reach of around 60% of viewers. That percentage is identified as a saturation point, and after it’s reached the brand will start to see diminishing returns. On top of that, there’s the concept of effective frequency, which is the number of times a company should invest in order for a customer to see an ad and respond to it. The embedded intelligence behind marketing mix model decisioning is based on an understanding of reach and frequency, which enables marketers to make better decisions and optimize their expense. eMarketer: How effective are these models at predicting how marketing drives sales? Krepsik: When the models control other factors that influence businesses, they produce a fairly strong level of accuracy. Our Benchmark Media Optimizer tool uses a marketing mix model, for example, and we typically make predictions within 5% to 6% of the actual in- market performance. eMarketer: In what ways can marketers take the insight they gain from marketing mix models and make it actionable? Krepsik: Let’s say I’m a brand owner and I’m trying to figure out what my media plan will look like next year. Perhaps I want to shift dollars to a digital campaign. What’s amazing is a marketing mix model not only allows marketers to make those budgetary decisions with really solid intelligence, but can also push those decisions forward into other activation platforms, such as the marketing cloud. eMarketer: What happens when a brand uses a marketing mix model from one vendor, but relies on a different marketing cloud provider? Do integration challenges arise? Krepsik: No brand owner in the world is going to use the same tool for everything. [That’s why it’s important to] build direct integrations to the buying platforms of choice, whether those are agency platforms or third-party platforms, such as the Adobe Marketing Cloud. eMarketer: What’s the next phase for marketing mix models? Are they going to become smarter and more accurate over time? Krepsik: We already know so much about how brand owners make investments in their media buys that artificial intelligence [AI] is the next phase. An AI prediction engine will be able to make two or three recommendations on media buys before even building a model. Rather, the prediction will be based on a brand’s profile and what is generally known about consumers in a specific category and in a specific country.
  • 8. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 8 Still Targeting Devices Rather than Users? Why that Is Problematic for Programmatic Marc Grabowski Executive Vice President, Global Supply and Business Development Criteo Marc Grabowski, executive vice president of global supply and business development at ad retargeting firm Criteo, spoke with eMarketer’s Lauren Fisher about the importance of taking a user-centric view when buying programmatically and shared his observations on the latest trends in header bidding. eMarketer: What are some of the big trends you are seeing unfold in the programmatic space today? Marc Grabowski: We’re seeing a number of things, but the first is mobile cross-device or omnichannel. We’ve obviously been seeing this area unfold for years, with revenues and purchase behavior moving over from desktop to mobile and tablets. We are continuing to see that in 2017. Criteo works with a lot of ecommerce and retail, and we’ve seen that the number of conversions taking place on smartphones is up enormously year over year. In our latest study, “The State of Cross-Device Commerce,” we found it’s up 41%, so a big number. That probably doesn’t come as a big surprise, but we are also seeing that the customer journey is longer and involves more devices than a lot of people previously suspected. “The customer journey is longer and involves more devices than a lot of people previously suspected.” A lot of people still look at things in terms of device view vs. user view. Device view is if you look at how people are interacting with the brand on a single device. User view is if you look at the user across all devices. We found that if you look at a device-centric view, about 43% of transactions take place in the first visit to a website. But if you look at a user-centric view, you see that it’s only 32% on the first visit. That means that, looking at a user across multiple devices along their journey, they have a much longer path to purchase than [if you look] at the user on just a single device. So it’s important for us to examine the value of that user and attribute that properly across those devices, because it then allows us to bid more for those users and find them in much more valuable areas than if we just took a single device view. eMarketer: Does moving from a device-level view to a user-level view substantially change your bid strategy? It seems like it would, given the numbers you shared above. Grabowski: In programmatic, it makes a big difference. We can bid more for that user because we can assure a higher value to an advertiser longer-term, because we know more about their user behavior. If we’re only attributing sales to a user on a single device, the challenge is we’re attributing too low. Instead of assessing a bid based on the likelihood for a user to convert on a particular device, we need to assess a bid based on the likelihood of that user to convert, period. If we look at a device-centric view of conversions in the US, we see about a 6% conversion rate. But if we look at a user- centric view, we see [that rate] go up to about 9%. That allows us to bid 1.4 times higher, and allows the advertiser to capture more value for that user when they’re bidding than if they were just looking at a single device. eMarketer: I know Criteo is very active in the header bidding arena today. What big trends are you seeing? Grabowski: We are definitely seeing that header bidding is important, and it’s a big topic. There are some benefits and drawbacks for header bidding. One of the big benefits is it brings a lot of demand forward for the publisher, and it’s definitely an advantage for savvy buyers. But it
  • 9. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 9 becomes very difficult for smaller, less sophisticated buyers to evaluate inventory across platforms, which is probably going to lead to greater consolidation it the space. “If we look at a device-centric view of conversions in the US, we see about a 6% conversion rate. But if we look at a user- centric view, we see [that rate] go up to about 9%.” When people were buying in the waterfall in the past, you’d see an impression. You’d evaluate the impression. Then you’d determine if you wanted to bid or not. But now, if you’re buying across multiple [supply-side platforms] SSPs as well as publisher direct, you might see that impression come up in 10 or 15 different auctions. It becomes much more difficult for buyers to understand where they should be buying that [impression] and what they should be bidding on it. Over the past year, we’ve actually had a lot of the [demand- side platforms] DSPs coming to us and saying, “Look, it’s getting more and more difficult for us to buy across multiple SSPs. Can you help us do that? Can you do the bidding on our behalf so that we can actually end up buying some of that inventory through you?” That’s been a big trend for a lot of companies, and I think it’s going to lead to greater consolidation in the next year or two. “Publishers are trying to figure out how to do server-to-server, but they just moved over to header bidding or to a wrapper and have now realized they have to make another move.” eMarketer: Many of the conversations about consolidation have to do with the transition to server-to- server header bidding, in which the publisher chooses a primary header partner though which the auction with all other header partners will run. There’s a lot of hype around server-to-server, since it enables publishers to take the auction out of the browser—thereby improving some of the page-load latency issues header has caused. Are you seeing many publishers transitioning to server-to- server setups? Grabowski: We see a lot of publishers asking questions, but we haven’t seen a lot of publishers make that move yet. There are definitely pockets where they have, and I think that over the next six to nine months, it’s going to pick up a lot of steam. Publishers are trying to figure out how to do server-to-server, but they just moved over to header bidding or to a wrapper and have now realized they have to make another move. It does take time, and a lot of publishers don’t have the IT resources to be able to roll out new infrastructure that quickly. Now the benefit for server-to-server is less latency, as well as potentially feeling less data risk and leakage. And as more inventory moves over to mobile, server-to-server is not only going to address the latency, but it can also serve in-app much better. There’s no question a lot of the space will move there, but it hasn’t moved yet.
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