YouTube Kids App - Part 2

Adding to the prior post on the YouTube Kids App, I wanted to highlight 2 aspects of the complaints against the app:

- "Many of the [unboxing] videos on YouTube Kids appear to be user-generated. Some, however, have undisclosed relationships with product manufacturers," reads the complaint. Unboxing videos are immensely popular on YouTube accounting for 20 Million searches alone last year. From one perspective, if the unboxing video truly provides entertainment and/or informative value to the viewer, then does it qualify as native content or an ad? Furthermore, if the unboxing video does not include a call to action to buy the product but simply concludes by showing the unboxing, can it still be characterized as an ad?

- Secondly, the complaint points out that videos and advertising on YouTube Kids are played in a continuous stream, counter to the TV rules that require a five-second "bumper" between ads and shows. The ads are certainly denoted as promotional considerations by the sponsoring brands, but the ads themselves purportedly come across as content such that the viewer (in this case a child) isn’t immediately aware that they are watching an ad.

Both these complaints hold weight (pun unintended). YouTube is definitely waltzing on the blurry lines between ads and content here. And it doesn’t help that the viewing audience is more gullible. This is another example of how digital, mobile-first guidelines need to be contemplated keeping these mediums and platforms in mind; and that advertisers will constantly push the envelope to break through to their audiences.

Foursquare powering Twitter's location library

Twitter and Foursquare announced a partnership this week where Foursquare is powering location-tagging in tweets. Essentially Twitter users can now tag their specific location using Twitter's new Foursquare-powered location library. Foursquare claims to be the "location layer of the Internet" or "the system that crawls the world with people in the same way Google crawls web pages with machines." In the last 6 years they have seen 7 billion checkins, 65M places, 250M photos, and 70M tips. Foursquare is trying to get users to checkin and 'location tag' because it will help make their location layer platform better much like how Google and Bing make their search results better each time someone searches for something because of a continuous feedback loop. Powering Twitter's location library is a significant coup d'etat because, well, Twitter sees 500+ million tweets a day and that is usage that will just make Foursquare's library that many times better. Why is this relevant to advertisers? Adam Dorfman from SIM Partners explains in his article:
http://www.simpartners.com/twitter-foursquare-partner-geo-specific-locations/

"The Twitter/Foursquare relationship creates an opportunity for businesses (such as large enterprises with multiple locations) to create more location-relevant information, such as offers and recommendations. For instance, if you Tweet about the lunch you are having in the Embarcadero Center in San Francisco, the Banana Republic Twitter account that you follow just might want to let you know about a sale going on at the nearby Banana Republic in the Financial Center. But retailers are not the only brands that can benefit. For instance, a medical practice might share with you information about the doctors at its location depending on where you are and what you are doing."

Location is one of the last critical pieces of information advertisers need to truly advertise customers based on context which is likely the next vector after intent (Google) and interest (Facebook). This news helps jumpstart that vector in a real way.

Predictive Advertising

Digital advertising is experiencing a converging trend towards true personalization (or personalization at the 'person' level rather than a customer demographic or segment level). It started by grouping search intents together so a 65 year-old man in Wisconsin shopping for a digital SLR camera was treated the same as a 15 year-old in Miami looking for the same search term. From there we saw demographic and action based targeting through Facebook and other platforms. And then retargeting enabled targeting a specific customer with their specific action. Ultimately, companies may 'pre-target' customers based on their profiles that are carefully created, nurtured, and monitored by brands says this article:

http://adage.com/article/digitalnext/retargeting-flawed-future-pretargeting/294113/

If a customer places a fresh direct order every other week, can agencies target them with a coupon from a competing grocery delivery service just before their next order? Or even better, can companies guess which product you want without you even knowing that you want it? A new shoe that you don't know is in the market is marketed to you because your digital profile computes that you are the ideal candidate to spend $250 on a pair. As machine learning advances, privacy concerns are mitigated, brands earn customer trust, and computational power and cloud services become omnipresent, one can see this future of predictive advertising.

No safe place to tweet

On Thursday Twitter launched 'Partner Audiences', a feature that enables advertisers to target twitter users based on their 'off-twitter' purchase and intent activity. In other words, Twitter’s Marketing Platform Partners, companies like Acxiom and Datalogix, create audience segments within Twitter based on information that that they collect from all over the Web. Twitter had a watered down version of the rich targeting data now available to its advertisers but Acxiom was nice to share some detail on its website (link below the excerpt):

“…these categories are selected by behavior, life stages, demographics and household information, and span all industries including financial services, retail, auto and consumer packaged goods…”

http://www.businesswire.com/news/home/20150305005947/en/Acxiom-Expands-Global-Data-Partnership-Twitter#.VPqKVlpE-C4

Technical details of the integration are sparse but one can assume (potentially at their own risk) that the customer data is anonymized and sensitive customer data is not transferred. Furthermore Twitter (ever so helpfully) points out that their users can simply opt-out of this feature from their privacy settings. And Twitter talks about how there is a minimum audience size so that there is never the chance that a single customer gets a personal ad (not personalized but personal i.e. one on one from the advertiser). In other words it was technically possible that this program allowed an advertiser to serve a single ad uniquely to one single user so that is the ultimate personalized ad. But Twitter disabled it because that would be too creepy. If you ordered a grande mocha Frappuccino from Starbucks with an extra shot, would it have been possible for Peet’s Coffee to advertise the same exact drink to you at half the price? I’ll let that percolate.

I think most Internet users know that there are companies with accessible names such as Acxiom and Datalogix making a living by aggregating online behavioral customer information and selling it to the highest bidders. But there is still something unnerving about the depth and breadth of this initiative. For instance, just Acxiom claims it provides a global addressable reach of 180 million Internet users, 300 million telephone numbers, and 1 billion physical and email addresses. Wow. Ultimately the efficacy of the program will weigh heavily on the reaction to this sort of integration.

Do Retargeting campaigns limit serendipity?

I was recently browsing the web when I started noticing books being advertised to me in the side banners. These were the same books, of course, that I had recently been browsing on various book retailers’ sites. One of them had decided to retarget me. At first I felt good: my web browsing experience had just been personalized. Indeed I found myself thinking about those books and whether I should pull the trigger on the purchase. But eventually it prompted to wonder whether now I was going to see only the things that I was looking for. In other words, discovery through serendipity was over. Newspaper editors are proud about the placement of stories and ads in such a manner that serendipity is maximized. A human mind thinks about how readers could discover a service or product that may not actively be seeking out. Is such a type of ‘editorialized serendipity’ extinct?

‘Look-alike’ campaigns where customers with similar profiles are targeted similarly may be one way to achieve discovery. In these campaigns, I will be presented with products and services that another customer (one that exhibits similar digital browsing, social and purchase tendencies as I do) has endorsed (by purchase or otherwise). There is a bit of targeted discovery here certainly. But a deeper level of discovery is still missing.

In fact, as more and more products and services become available online and digitally, the need for discovery deeper into the catalog (whether it be books, clothes, accessories, etc) rises. Platforms like Amazon rely on the customer spending time on their site to achieve the deeper discovery through browsing and taxonomy. But given that Google and Facebook are becoming the highway system by which we navigate our digital lives, a case can be made that advertisers have an opportunity to bring the deeper level of discovery to their target audiences through ads. And in doing so, create a richer, discovery-led advertising experience.

Contextual Advertising

I was reading this article about how Oyster, a "netflix for eBooks" app, recently updated their recommendation engine to include contextual recommendations:

http://thenextweb.com/apps/2015/02/17/oyster-updates-app-focus-contextual-book-recommendations/

The gist of the article is that depending on the time of the day (for example) users will be recommended different titles. It made me think about how contextual recommendations could make their way to advertising. Imagine if display advertising could change depending on the time of day, what the weather was that moment, and perhaps even be location-aware. If display ads could be smart enough to start advertising umbrellas when they know its about to rain, then advertising starts performing a utility function for the user. The lines between advertising and immediately-useful-recommendations begin to blur. Certainly search-based advertising already has the potential to be very utilitarian for the user (because it is so intent-based), but their utility is limited by the instance of the user query. Contextual advertising has the advantage of personalizing the ad to potentially going the next step and actually being very useful for the user. Will advertisers go down that route and invest in the necessary algorithms and computing power to serve personalized ads to the hundred of millions of potential ad viewers out there? If initial testing show increase in conversion, then this could be a race for startups and big firms alike.

What’s the right go-to-market strategy for Augmented reality?

A couple of years ago, it appeared that Google glass would herald the dawn of augmented reality. It fizzled out with as little notice as the fanfare with which it launched. Recently Microsoft launched their version called HoloLens:

http://wallstcheatsheet.com/technology/what-augmented-reality-is-shaping-up-to-look-like.html

Google Glass delivered augmented reality via a small screen that superimposed images and data on whatever it was that the user was viewing. HoloLens promises a more immersive experience where the user’s entire field of view is an augmented reality driven experience. What is the right go-to-market strategy?

Google’s product lends itself to quick data look-ups superimposed on the viewed object. And Microsoft’s focuses on immersive game-like experience or complex workflows (3D computer aided design for example). At least in this interpretation each company, Google or Microsoft, has created products that advance their respective core competencies. At the risk of over-simplifying, these two offerings may be viewed as being on a spectrum of casual use-cases to heavy-duty use-cases. This type of spectrum is seen in the gaming segment where casual gaming acts as the counterbalance to traditional, immersive video games. If the gaming analogy is a blueprint for how augmented reality will “go to market”, Microsoft’s entry is a more classic play of going after the enthusiasts in the vertical (i.e. lead users and enterprise users). Once the technology catches up and the core applications and audience build out, augmented reality may have a shot at wider adoption, which in turn would lead to an entire industry complete with developers and advertisers.

Digital Marketing in an IoT World

In reading a recent article about the Internet of Things (IoT) as explained by technology pioneer Tim O’Reilly, the one thing that jumped out was a mention of Google Now as a all-knowing, context-aware, predictor app.

http://bits.blogs.nytimes.com/2015/02/04/tim-oreilly-explains-the-internet-of-things/

O’ Reilly’s point is that we’re in the early stage of IoT adoption; that once more and more everyday things have sensors and wireless communication we will see transformative experiences in our daily lives. Uber, he says, is an early IoT company where both the driver and the passenger are now enabled to communicate in a real-time, context-aware manner (context in this case being location). The article’s meta point (for me anyway) is that once the ‘things’ from the Internet of Things are wired (or more accurately wirelessly wired), there will be a tremendous amount of data that gets fed back to the humans so that they can make a decision. Or to O’Reilly’s point some data cruncher that manages the entire operation thereby providing context and personalization to the human (or customer). Fascinating stuff. But the mention of Google Now towards the end of the article caught my eye. Once Google Now gets more and more inputs from IoT-enabled devices it has the potential to be a very clever predictor app that can deliver context-aware suggestions to its user. Viewing this from the lens of digital marketing one can see how Google Now could serve ads in this paradigm or perhaps more powerfully extract fees from merchants and brands to surface their wares meaningfully within these powerful context-aware suggestions. The next big monetization wave? Or something incremental or natural given current digital marketing trends? As long as it provides value to the consumer, I predict strong user adoption.