3 Ways to Adapt to the Shift Toward Online Privacy (Ethically, Nonetheless)

This post originally appeared on the Umbel blog. The Umbel Marketing team helped edit and refine the original content.

In May 2014, the E.U. announced that search engines were responsible for removing links deemed inadequate or irrelevant. This rule is also known as the Right to be Forgotten, and fell squarely in the crosshairs of a Google lobbying campaign. Since then, Google has received over 160,000 requests to remove content and there are few signs that the requests will slow down.

Yesterday, Mozilla announced the Forget feature in the latest version of the Mozilla browser, which removes cookies, form field information and web browsing history. Of course, this feature is available in Incognito mode on Chrome, but Mozilla is the first major browser to place such a feature front and center of its newest product.

The E.U. made a decision for regulatory purposes. Mozilla made a decision in the similar vein to satisfy a desire to not hand over all personal information to ad networks, data brokers and the assorted acronyms of companies that exist to monetize the information we unwillingly share. No matter where the next push to online privacy comes from, it’s a push that will continue to emerge until tracking software becomes obsolete. The push may be congressional; it may come from the media industry (Google, Facebook, etc.); or it may come from the people themselves demanding more privacy.

The truth is plain to see: we’ll all have to adapt – and the sooner we get used to it, the better. Online marketers, ad ops specialists, salespeople and the like will eventually have to perform their day-to-day functions a little bit differently, respecting the privacy of their both their customers and those with whom we all share the web.

Thankfully, there’s a way to get started today.

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Tech Giants and The Power of “The Feed,” or Why Algorithmic Accountability is Needed Now

This post originally appeared on the Umbel blog. The Umbel Marketing team helped edit and refine the original content.

On August 20, Dick Costolo, Twitters’ CEO, announced that his company would suspend all accounts that shared the gruesome beheadings of journalist James Foley. The internet cried censorship whereas news organizations argued that Twitter’s CEO exercised standard editorial rights. The Guardian stated that for “the first time, Twitter acknowledged it was a platform that exercises editorial judgment.”

Twitter, fundamentally, is a company that monetizes the distribution of content. Their model is the same as that of Facebook, Google, The Guardian and the New York Times. But as of August 20, Twitter has more in common with The Guardian and the New York Times than it does with a Facebook or Google – because now it discloses its editorial judgements.

On the other hand, Facebook and Google operate in black boxes, shrouded by advanced algorithms that encourage us to gradually consume more information and generate higher ad revenues. These companies disguise their lack of accountability by arguing that they know us better than we know ourselves. They can predict the news we’d like to see better than we can on our own accord, or so they say.

And this approach might work right now, but these companies should exercise what they preach in their PR materials – that is, openness and accountability. Doing so is easy and has no material harm on their businesses. If anything, it’ll ignite the same debate caused by Dick Costolo and force us to think more about the types of information we consume and the methods by which we receive it.

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The 3 Biggest Problems with Salesforce’s Analytics Cloud

This post originally appeared on the Umbel blog. The Umbel Marketing team helped edit and refine the original content.

Salesforce isn’t satisfied with its $32B market capitalization. It wants a slice of the $42B business intelligence industry, currently dominated by major companies like Tableau, Domo, Microsoft, Oracle and SAP. How so? Well, Salesforce recently introduced the Wave Analytics Cloud, a product that will let companies connect data from different systems, visualize that data, and allow users to make actionable decisions from insights found in that data. This is themain business proposition of many big data BI companies.

Of course, these visualizations are not meant to be incredibly sophisticated but to rather help standardize business operations. According to the New York Times, “the application was able to look at a national sales force, quickly sort it by people and regions, then figure out where there were big disconnects between budget targets and actual results”

Despite its splashy entrance and enormous brand presence, the Wave Analytics Cloud will face many of the same pitfalls that its competitors face – limited data access, lack of a dedicated staff to use its robust functionality, and limited actionability.

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Amazon’s Data-Driven New Media Strategy: Bring Broadcast Ad Spend Online

This post originally appeared on the Umbel blog. The Umbel Marketing team helped edit and refine the original content.

Amazon has long been open about its efforts to displace our reliance on overpriced cable. After all, an Amazon Prime membership includes Amazon Prime Video, which comes with native and re-aired programming.

Last week, though, Amazon expanded its efforts by getting into the TV ratings business – and this is a really big deal. First of all, TV ratings typically work as follows:

  1. Writers pitch their ideas to shows and networks. Networks purchase the ideas and pay writers to write the first episode
  2. TV producers and executives read all of the scripts and they choose a small number of them to actually create (produce)
  3. Pilots are then focus tested with a series of professional and paid testers. Shows that make the cut (at least a full season) rely on the pilots passing the expectations of paid testers and a handful of television executives

For Amazon, the company has its eyes set on the testing component. They’re releasing pilot episodes of five different shows and getting feedback in the best way they know how – their beloved five star ratings system.

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The Social Login Debate – and LinkedIn’s Weird Absence

This post originally appeared on the Umbel blog. The Umbel Marketing team had a major role in editing and refining the original content.

The trend toward social login – and improved user experiences – continues across the internet as Facebook and Google+ compete for a larger market share. Publishers, game developers, retailers, brands, agencies and aspiring bloggers such as myself see an enormous opportunity in social registration. Facebook is the clear leader in this category and has a solid 55% market share. Google+ is a distant second with 27%. Yahoo and Twitter have 11% and 5% respectively.

But our favorite professional network, LinkedIn, is nowhere to be seen. For the past year, LinkedIn’s social login product has consistently held 1% market share, and their reasoning for such is clear – they don’t need to have more. Unlike LinkedIn, Facebook, Google and Twitter make an overwhelming majority of their revenues from their advertising products. Their ads rely on two vital pieces of data, user volunteered and user collected.

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Let’s Get Tactical: How to Make Your Department More Data-Friendly

This post originally appeared on the Umbel blog. The Umbel Marketing team had a major role in editing and refining the original content.

It seems as though the entire world is abuzz about big data. If you get data alerts from Google much like I do, these are the headlines that fly over your radar every day:

  • Chinese Data Don’t Add Up [WSJ]
  • Can Data Analytics Make Teachers Better Educators? [CIO]
  • Scientists Question the Big Price Tags of Big Data [Newsweek]
  • According to U.S. Big Data, We Won The Vietnam War [Forbes]
  • Can Big Data Cure Cancer? [Fortune]

In other words, big data is doing big things – or it isn’t. That’s the general sentiment across all industries when it comes to the topic and many professionals are coming up against the same questions: Is big data worth it? Does it produce ROI? Is it just a phase? Will data become an asset? Who are the major players? Does any of it matter?

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Steer the Ship

“One of my clients can’t launch their AdWords campaign without this feature” — Client Services

“What feature?” — me

“Dropping pixels in the Activators. They want to launch ASAP.” — Client Services

That feature was planned for an upcoming sprint, likely sometime in Q3 2014. I had spent a little bit of time researching product requirements, but they were not polished enough to hand to the engineering team. To make things more complicated, our Director of Product Management was out of town.

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Balancing User Privacy & Data Monetization

This post originally appeared on the Umbel blog. The Umbel Marketing team had a major role in editing and refining the original content.

I don’t remember the last time I signed up for a service expecting to pay for it. There might have been a freemium component involved (pay for a basic service, receive constant offers to upgrade), but it certainly did not require payment up front. The assumption was pretty evident – they were going to use my data to generate revenues and hopefully make my experience better.

As the number of connected individuals increases, so does the volume of data and the necessity to make sense out of it. In parallel, data-collection-as-a-revenue stream (DCaaRS, see we can make up acronyms too) becomes more popular as well.

After all, in our current digital age, services (like Facebook, LinkedIn, etc.) seem free, but we’re paying with our data. Users understand this and are right to be a little hesitant. How do any of us know that a particular app maker is ethically respecting our data?

In truth, companies have been packaging and selling consumer information since at least the 1960s. Axciom was one of the first. They anonymize personally identifiable information and sell it in bundles to anybody with a credit card. App makers, publishers, game developers, and really anybody but brands have begun to rely on the same model. Collect as much information as possible about a user, de-personalize the data, package it, and sell it to the highest bidder – usually a data broker. Sound creepy? These are the same companiesunder congressional investigation.

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The New “Subscriber” is a Click-Bait Addict – But There’s a Way to Turn it All Around

This post originally appeared on the Umbel blog. The Umbel Marketing team had a major role in editing, redrafting, and refining the original content. 

In my never ending quest for zero inbox, I find myself unsubscribing from quite a few emails. Whether they land in my primary, social or promotions folders in Gmail, I receive way more junk than I would like – even including Google’s built-in spam filter, which has gotten much better over the years.

To be honest, the only emails I actually want to receive are updates about my Amazon orders, the Crunchbase daily newsletter about startup funding, and a few miscellaneous business-related newsletters within the Austin area. I get the remainder of my content –New York Times, Wall Street Journal, TechCrunch, Quibb, Google News – by subscribing.

Of course, I don’t mean “subscribing” in the old school sense or even in the way most of us think about subscribing now. I don’t receive a paper on my doorstep every morning, nor do I receive newsletters from any of these publications.

Instead, I vote with my mouse.

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Conflict and Surprise: Big Data’s Big Storytelling Potential

This post originally appeared on the Umbel blog. The Umbel Marketing team had a major role in editing, redrafting, and refining the original content.

“There are 4,448 active sessions on my website right now. Earlier, I had 1,502 active sessions. Currently, 65% are returning and 35% are new. Coincidentally, 35% of the audience is also coming from mobile right now, and since my site cookies don’t work on mobile, it’s safe to say that I actually have fewer new visitors than my analytics is showing.

OK – the NBA Finals GIF appears to be popular, as is the US-Ghana piece, though it doesn’t look like the traffic now is consuming as much content as the afternoon traffic usually does.”

This is a typical editor’s thought process and afternoon analysis on site content, and it’s a critical step to optimizing a website on which revenue depends largely on ad impressions. Unfortunately for this particular editor, the morning didn’t go so well.

“The higher-ups won’t be happy – we were supposed to have 5,500 uniques this morning alone, and an average pages per visit of 3.4. This will certainly impact our ad revenue for the morning. I can make a few adjustments to the copy and imagery on the page, but it is unlikely to make a huge impact, especially since its been a couple hours since publication.

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