Month: May 2019

Target will take lessons learned from these startups to adopt new tools and technologies that solve for pain points like connecting customer data between online and in-store, real-time product recommendations and personalization. It’s a better alternative than outsourcing this work to vendors, which separates the retailers from their customers, risking security and a loss of control.

In its accelerators, Target has the power. For participating startups, the accelerator comes with a $120,000 investment from Target, an eight-week program and a Demo Day pitch to Target executives. The Target Incubator offers a $10,000 stipend and space to work on Target’s campus. Selected startups get to pilot their technology in Target stores following the accelerator, but formal partnerships aren’t guaranteed. The startups chosen touch on a variety of retail problems to be solved, including chatbots, AI, inventory and merchandising management and analytics, last-mile delivery, mobile payments, customer insights and retargeting. All of these solutions operate off required customer data, including insight into how often customers visit stores versus shop online, how they’re using the Target app, how fast products are selling and what customers are searching for.

“Working with startups gives Target the opportunity to consider testing outside innovations that might someday help us enhance our assortment and guest experiences,” said a Target spokesperson in an email. “In exchange, the startups get access to many of our resources — including mentorship, expertise and programming to help them ultimately learn how to scale their business to reach mass retail.”

More specifically, Target’s partnerships with the startups it chooses to work with after the accelerators end help it improve its own in-house data technologies. Target’s data and analytics teams are all in-house: The company doesn’t share its first-party customer data without outside vendors that would need access to that data to work with a retailer, like a CRM company. So long as Target builds out new retail solutions around evolving customer needs and behavior, it’s doing so on its own, with companies it acquires (like the last-mile delivery provider Shipt) or partners with through its accelerator programs.

“We protect our customer data, meaning we don’t partner with outside vendors if it means we need to share that data,” said a Target employee speaking on background. “Security plays a big role in our data strategy, which can make it hard, because we have to do it ourselves. So we look to our accelerator startups to fill that role.”

Increasingly, retailers want to stake a bigger claim in technology companies rather than simply hire them as service providers. It’s a competitive advantage to own tech solutions, rather than outsource them to vendors who have a laundry list of other clients. Companies like Walmart, Nordstrom, Kroger and McDonald’s have acquired technology companies over the last three years that speak to their own strategies, and what’s worth buying versus building in-house or outsourcing. In acquisitions, customer data plays a central role in the tech services provided: Earlier this year, Walmart bought an AI solutions company that mines customer reviews for product recommendations, while McDonald’s bought Dynamic Yield, a marketing analytics platform. Nordstrom last fall acquired two customer service messaging systems that can connect employees directly to shoppers.

In addition to Shipt, which it acquired in 2017, Target acquired same-day delivery management platform Grand Junction the same year.

“These types of acquisitions reinforce the point that retailers of all shapes, types and sizes are trying to leverage technology as a competitive advantage and use it to close the elements around customer experience gaps,” said Brian Cleary, vp of marketing at RedPoint Global, a customer data platform. “But there’s a lot of experimenting behind the scenes of acquisitions — retailers are setting up startup labs to evaluate technology they might want to invest in. Whether they’ll build or buy it doesn’t really matter, but what these labs do is help retailers to operate in new areas, like personalization.”

Target’s accelerators bring retail-tech startups closer to the company’s chest, letting it see new technologies in action and then decide whether or not to formalize a partnership. Last year, six companies of the nine that went through the summer accelerator went on to pilot their technologies in Target stores. Those included Sozie, a user-generated content platform that specializes in helping customers find the right size online, and Satisfi Labs, an AI response platform that sends real-time answers to customers shopping in Target stores.

The Target employee said that the startups Target works with in both the accelerators and following pilots help it to incorporate new types of technology into its data strategy, and target new types of customers.

“It’s about new customer acquisition and closing the loop while still owning all of our own data,” the employee said.

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“By and large, keywords are still a pretty blunt tool to use,” said Andrew Goode, evp and head of programmatic at Havas Media North America.

Vice recently drew attention to the issue of keywords being too blunt a tool. At the publisher’s NewFront presentation on May 1, Vice announced that it will no longer allow ads to be blocked from running on pages containing keywords such as “gay,” “Asian,” “Muslim,” “climate change,” “immigrant” and “fat.” While agency execs applauded Vice for taking a stand on the issue, they are wary of individual publishers making such judgments on behalf of advertisers. “Brand safety is and always has been a subjective area,” said Goode, who advocated for advertisers to look beyond just keywords when it comes to brand safety.

Nonetheless, keyword lists continue to be an important component of advertisers’ brand-safety measures; Goode described them as “the final filter rather than the only filter.” But to ensure they are an effective filter, they need to be more refined in their application so that an advertiser is not avoiding all articles containing the term “gay” but is making sure not to support the ones that are using it in a derogatory way. “It’s those semantic combinations that really matter,” said Joe Barone, managing partner for brand safety in the Americas at GroupM.

Agencies, such as GroupM, Havas Media and Publicis Media, have been working with ad verification companies to take better consideration of context when deploying keyword lists to protect clients’ brand safety concerns. Those efforts began a few years ago by applying semantic analysis to advertisers’ keyword lists in order to look out for other words on the page that can indicate the context in which the keyword is being used. “The next step is sentiment analysis,” said Barone.

Verification vendors can use sentiment analysis to evaluate whether an article is positive or negative in relation to a given keyword when determining whether an ad should or should not be blocked from appearing on the page. “Some of the newer approaches that the verification companies are employing are designed to identify the nuance in the sentiment as opposed to the raw keyword,” said Barone.

Sentiment analysis can be used to make judgments when an article’s sentiment isn’t binary. In addition to judging articles as being positive or negative, an article can be categorized as neutral, which would be OK for most clients though not OK for risk-averse advertisers, Barone said.

However, sentiment analysis comes with its own complexities. To analyze whether an article is positive, negative or neutral, a sentiment analysis tool may need a wider array of information than the article itself, such as the comments on the page and metadata related to the images or videos that also appear on the page. Verification vendors “have sentiment analysis tools, but they don’t have support from the publishers to provide a consistent framework of metadata to do the best possible sentiment analysis that they can,” said Yale Cohen, evp of digital investment and standards at Publicis Media Exchange.

Given all the information necessary to provide the most accurate sentiment analysis, applying sentiment analysis to advertisers’ keyword-based blocking at scale remains “a ways off because it takes a lot of content categorization,” said Barone.

However, publishers would be incentivized to cooperate with that content categorization, if only to ensure that they are not being unfairly evaluated for brand safety. “What we’re looking for would be a common categorization engine because we want to treat all publishers equally,” Barone said.

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The contrast between a struggling albeit robust linear advertising business and a growing yet fragmented online audience shows why ITV has finally set in motion plans to effectively build its own ad tech. Owning this technology, means advertisers will be able to buy ads around ITV’s VOD content in the same automated way they do from the likes of Google and Facebook.

Since revealing the ad tech plan with Amobee last month, ITV’s commercial execs have kept a low profile, according to agency executives interviewed for this article. What little information the broadcaster has shared with ad buyers to date points to a pitch that will try to balance the need for detailed viewer data and transparency to make it work, that includes knowing a lot more about the viewers than just their age, sex and income.

“It’s always been hard to get to a high-value audience within broadcaster VOD because a lot of the targeting has been limited,” said Lawrence Dodds, communications and planning director at UM London. “What ITV are doing could change that and potentially allow us to target bespoke third-party segments and even first-party segments.”

Online advertising is new territory for ITV’s commercial team, which is going through a process of internal education and recruitment. Agencies have, in turn, found it hard to pin down the relevant people to clarify the ad tech pitch. It is already on the lookout for data specialists who can mine and sell audience data as well as broker new partnerships around it. Whatever ITV develops around its own first-party data has to rival the kind of detailed segmentation and profiling that Sky already offers to the likes of Argos that have their own first-party data they combine with the broadcaster’s own. New commercial execs are also on the way at ITV as the broadcaster’s pitch comes down to selling additional content to programmatic traders in the hope they move money away from Facebook and YouTube.

Like all addressable pitches, the early selling point for ITV is the ability of its ad tech to eliminate waste. The issue, however, is that being targeted means dealing with smaller numbers of audiences than what could be reached on linear TV. But according to some ad buyers, that’s a more palatable trade-off if the data they buy allows them to drive incremental reach on larger campaigns.

“It seems ITV views the two things that could drive online video and TV will be content and data, which are assets they can own,” said Gregor Chalmers, associate director at The Specialist Works. “There is no question that this is the correct and logical step for them to take. The questions will all be over the execution.”

ITV is late to the party with its own addressable plan and based on the limited information it has shared with ad buyers it could go two ways: The broadcaster will come to market having learned the mistakes of other platforms and have a fully functioning service that gives advertisers the control over issues like verification and data they demand.Or ITV will go through a process of refinement that means the market doesn’t see a truly addressable offer for another year or two. Given ITV Hub streams linear TV and can only be used via an app on a smart TV, it won’t be possible to target ads directly on the screen unless it uses HBBtv, a common standard already used for the BBC’s Red Button and Freeview Play, which the broadcaster has not clarified.

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In the last three months of 2018, the average number of blocked ad impressions decreased slightly to 10.2%, compared to 12.8% in 2016 when rates were at their highest. Looking specifically at desktop, blocked impressions have fallen slightly to 21.6%, 22.5% during the previous three months. Mobile is still growing but from a small base. Currently, 2.4% impressions are blocked, per AOP, compared to 0.4% in 2016.

Despite this, the amount of lost revenue is increasing as the number of total impressions publishers serve has risen. The AOP estimates that the median annual publisher loss is nearly £950,000 ($1.2 million) in revenue due to blocked ad impressions. Across all 11 members audited, this totals nearly £18.4 million ($23.9 million), up from £10.9 million ($14.2 million) in 2016.

However, set in the context of publisher growing revenues overall, and the overall increase in total impressions served, this slight increase is to be expected, according to Richard Reeves, managing director at the AOP. “The threat of ad blocking is being contained and understood rather than solved, and you need information to do that,” said Reeves.

Three years ago, the fear around ad blocking was far more pronounced. At the time, publishers struggled to grasp the impact or scale of the problem. The AOP’s audit examines the effect to publisher bottom lines, rather than the potential publisher impact that studies on how many people install ad blockers would have. For instance, one study from firm Visual Objects that surveyed 500 ad block users found that 60% of them whitelist sites, leaving publisher revenue intact.

For the most part, intrusive ad formats have been filtered out by platforms paired with publishers understanding they can improve user experience to offset people blocking ads. “I’m heartened to see the impressions being blocked is this low,” Reeves added.  

Display ad revenue across AOP publishers grew by 8.5% in 2018, according to Reeves. The Interactive Advertising Bureau and PwC announced at the end of April that U.K. advertisers spent £13.4 billion ($17.4 billion) on digital advertising in 2018, a 15% year-on-year increase. The IAB figures include growth on spend on platforms like Facebook and Google, and so is higher than the AOP’s.

“We have to remain focused on the situation occurring in mobile use,” said Reeves. Three years ago, the panic around a potentially crippling growth in mobile ad block rates didn’t fully materialize. Although Reeves is aware of not reading too much into the growth in mobile ad block rates, more growth is still expected but not to the same extent as on desktop.

“We’ve absolutely seen an increase in mobile ad-block rates over the last year,” said Nick Flood, managing director, Dennis Digital. “These are now in the very small single-digit area, and I predict this will continue to grow as consumption habits continue to shift to mobile.”

Methods of measuring ad blocking have improved as blocking ads and the different units have become more sophisticated and broadened out beyond just display ads.

Primarily though, post-GDPR publishers have been on a steep learning curve about the importance of managing their relationship with the user, the value of their first-party data and how this informs style, tone, execution and consent strings.

“The ad-blocking conversation has been absorbed into the larger consent conversation,” said Reeves. “It still needs to be front of mind, but publishers are required by law to be more explicit with data gathering and activity, the function and delivery of ads and the purpose in which they’re served.”

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