Facebook tells senators it still uses location for ads despite user location services opt-out


Greg Sterling

We might soon see another FTC investigation of Facebook for “consumer deception.” The company acknowledged in a letter to two U.S. senators that it continues to capture and use location to serve relevant ads even if users have turned off location services.

Bipartisan inquiry into Facebook’s user of location. Senators Coons and Hawley sent a letter in November to Facebook “raising concern that Facebook ignores the wishes of users who don’t want their exact location to be tracked,” The Hill first reported.

Facebook, in September, pledged to be respectful of user choices around location tracking. In a blog post, the company said, “You can control whether your device shares precise location information with Facebook via Location Services, a setting on your phone or tablet. We may still understand your location using things like check-ins, events and information about your internet connection.” So Facebook is explicitly saying it will still use location.

Facebook not technically ‘deceptive.’ This caveat and the word “precise” may wind up saving Facebook from legal consequences. Mirroring the language in its blog post, the company explained in response to Coons and Hawley that it continues to use location (though not precise location) from other sources such as user check-ins and IP address. So, as laid out in its post, the company isn’t technically “deceiving” people, though they may not have caught that point.

Google was similarly embroiled in controversy over location tracking after it was discovered that the company captured user location even if location history was turned off. Google subsequently made changes and offered more transparency and user control over user location.

Why we care. As an aside, research has shown that locally relevant ads outperform ads without location. People generally prefer “relevant” ads. The real issue here is trust; and on that question, Facebook is still in the dog house. The company continues to struggle following the post-2016 revelations surrounding Cambridge Analytica and the exploitation of user data by third parties on the platform.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.


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Taboola Trends launches to offer free ‘A/B insights’ into video, image, text creatives


Greg Sterling

Content discovery platform Taboola, which two weeks ago announced a merger with its primary competitor Outbrain, recently released a trends tool that offers insights about the performance of ad and content creative from its publisher network.  

The combined company has roughly 20,000 publisher customers and 10,000 advertisers in 50 countries. It also claims to reach 52% of all desktop users globally.

Slice and dice by country, platform and industry. That global traffic data informs Taboola Trends. It’s a free tool to gain A/B-style perspectives on image creative, video content performance, keywords and titles.

Marketers can look at image creative by industry, device category, language and country. You can then see how variables such as text, color, subject, model gender and image type impact click-through rates. In the example below, the black and white image somewhat surprisingly outperforms the color image with an 83% better CTR.

Source: Taboola Trends

Similarly, with video, marketers can see the video types that are more likely to be completed, by content category, country, device platform and duration.

There’s also trend data tied to keywords and phrases. In addition, marketers can test alternative headlines or image titles and see relative CTR performance estimates. Finally, the company also offers summaries of vertical-specific insights in industry benchmark reports (registration required). Though interesting, not all of this information is equally useful.

Source: Taboola Trends

Why we should care. Taboola Trends joins Google Trends, BuzzSumo, Answer the Public and other free tools that offer research and insights for marketers seeking ideas, inspiration and context as they plan campaigns. But other than the title analyzer, Taboola Trends is not a true A/B testing tool for your individual content or ad creative. It does provide, however, a kind of directional predictor of CTR performance that can be helpful in thinking about content and creative.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.


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How we can restore trust in digital advertising


Greg Sterling

Benoit Grouchko is CEO and co-founder of Teemo.

Teemo is a France-based location intelligence provider (“drive-to-store” marketing platform) that serves the retail, fast-food, automotive and grocery industries. The company worked closely with the French privacy regulator (CNIL) to develop specific consent language around third-party use of location data and saw 70% consumer opt-in rates.

Benoit Grouchko is CEO and co-founder. I spoke to him recently about data and consumer privacy and his expectations for how CCPA will impact marketers.

ML: Google proposed an industry-wide initiative to try and preserve behavioral targeting in the U.S. while giving consumers more control over that data. Are you hopeful about this effort?

BG: Google
owns such a large piece of the digital advertising pie that one can only be
hopeful. Do they have the leverage to manipulate this to their benefit? Sure,
but their efforts can also do a lot of good on a macro level. 

It’s a good
sign and indicates that Google is seeking to be ahead of the regulation curve
by setting the precedent on privacy. What’s interesting is that a lot of the
best practices this blog proposes are already in place in France and the rest
of Europe. There’s a lot the US can learn from GDPR.

ML: Many surveys suggest that consumers increasingly distrust big internet companies, brands and digital advertising generally. Can trust in digital marketing be restored?

BG: I am an
optimist so, yes, I think trust can – and will – be restored. We sometimes
forget that digital advertising is a relatively new industry. And every
industry goes through a “correction” or “adjustment” of some kind at some point
in its history. We’ve been building up to this for a while now; the Facebook
debacle and the institution of GDPR are the two straws that broke the camel’s

I think
it’s a matter of time until things settle. I can’t say it will be soon, but
regulation will normalize over time and companies will fall into place. 

What we can
do individually – as people and companies – is to do what’s right for our
customers and to organize. We need to stop thinking of short-term gains and
think about the ecosystem as a whole. As you rightly pointed out, we all stand
to lose here. 

consumers conflate mistrust with misunderstanding. Better transparency will
help people see that the “creepy types of targeting” they mistrust is not quite
as threatening as they perceive.

Advertisers are good at their jobs,
and even better when they use data. Being embedded in the ad industry, I have
the perspective that good advertising helps inform me about products or
opportunities I wouldn’t otherwise know. As digital literacy and transparency
increase, so will trust.

ML: We spoke about finding a middle point between irrelevant and creepy. In a post-GDPR, CCPA world how does all that happen on a mechanical level? 

BG: The middle
ground between irrelevant and creepy is an ad experience that optimizes
performance for the advertiser and is great for the consumer. Two things need
to happen to find that middle ground: first, advertisers need to get better at
understanding performance. Even if an ad is hyper-relevant, if a consumer
perceives it as creepy, it will decrease performance and deteriorate brand
sentiment. Advertisers need to look at performance over everything. The “creep”
factor will play into performance and help advertisers determine what types and
depth of targeting to use.

The second thing that needs to
happen is on the consumer level. Consumers need to become more digitally
literate. Any data that digital marketers ethically use will be anonymized.
Most consumers probably don’t understand that. It goes both ways, though. Many
consumers don’t know which apps are tracking them and when. Great transparency
and knowledge will help us reach a middle ground.

will certainly help put some boundaries there and make sure nothing creepy
happens. However, there is a deeper question here around what is actually
creepy or not, as that might vary from one consumer to another.

ML: My understanding that most Europeans aren’t doing much in the way of managing cookie settings; they’re making binary choices (decline/accept). Is this accurate? 

BG: I think
European consumers are confused about how cookies function. I also think many
are wary of the concept. And they should be.

companies use “tricks” to drive consumers to give consent. Some play with
screen placement and colors; others offer only a single choice, which is

From my personal point of view, I think these choices relate back to digital literacy. More digitally literate people will make more complex choices and set their permissions at the top level. Most people are probably making binary choices, but as digital literacy increases, people will begin to change their attitudes. Pop-ups were once the bane of any Internet user’s existence. Now users have to deal with privacy, notification and tracking pop-ups. I doubt this will continue forever.

ML: Regarding CCPA, what is put in front of consumers when they visit a website will matter. If choices are complicated they’ll likely “accept” to get to the desired content and there won’t be much impact. Do you agree? 

BG: I couldn’t agree more. And it’s these manipulative/deceptive practices I stated above that are counterproductive to the cause. 

No one reads the entire terms and conditions. People use the Internet to increase speed and efficiency. Like I said, even the opt-in or opt-out choices may fade away at some point.

ML: In the U.S. “ad choices” — the industry’s prior attempt to deliver user control and choice re behavioral targeting — is a total failure.  Why would any of the newer “choice” initiatives (or CCPA) be any different?

BG: Something’s
got to give in terms of privacy and transparency in the US. I hope that CCPA
will learn from GDPR and how consumers reacted. While the first set of
regulations may create an undue burden, the landscape will reach equilibrium,
and everything should go back to “normal” at some point.

ML: How does Safari and ITP, which is a different approach to these same problems, affect the market? Many marketers see cookie blocking as a blunt instrument and very heavy-handed. How do you see what Apple is doing? 

BG: Apple has
always taken a hard line on security – and it’s served them well. If there were
more companies like Apple, perhaps we wouldn’t be in this situation to begin
with. The greedy argument is that digital advertising would not have reached
such heights but, as I said, this is a long-term game. 

The problem
I see now is that everyone has gotten a taste of the profits and set the bar
quite high, making it difficult for any one vendor to take such a hard line
without losing a ton of business. Not an easy problem to solve.

While a
hard line on security has served Apple well, consumer reaction always has a lot
of influence on regulation. Apple has always been able to simplify the digital
experience for consumers. But I still think this first round of guidelines will
be a learning experience, especially as other big players in tech respond.

ML: Whose job is it to educate consumers to make them more digitally literate? 

BG: I think, ultimately, it’s up to us in the industry to not only do what’s right in terms of respecting privacy but also to educate consumers on best practices. I feel that regulation is meaningless to consumers if they don’t understand the nature of the transactions in which they engage, how the technologies work, and the associated costs, benefits, trade-offs. 

Informed consumers are in the end
the future of our businesses, which are built on trust. It’s in our best
interest to do right by then to gain/regain this trust so we can build loyalty.

Regulators, advertisers, companies,
and web providers all have an obligation to be transparent about the digital
landscape and what it means for consumer privacy. But, if the burden falls to
these entities it creates a greater layer of complexity than necessary. It begs
the question: how much should regulators, advertisers, etc. inform consumers?

There certainly should be some
level of transparency, but privacy practices that, for example, initiate pop-up
requests for permission to run every nominal background task may end up
annoying or confusing consumers more than they help them. The landscape will
eventually reach equilibrium. Ultimately, in any society with freedom of
information, it’s up to consumers themselves (along with news organizations,
journalists, and watchdogs) to become digitally literate.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.


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Does the 9th Circuit’s new decision in HiQ vs. LinkedIn open the floodgates to scraping?


Greg Sterling

Yesterday the U.S. Ninth Circuit Court of Appeals found (.pdf) in favor of data analytics company HiQ Labs, which had been scraping data and building products from LinkedIn public profiles. It’s a case that has a lot of implications — and may still be appealed.

CFAA and anti-hacking rules. LinkedIn tried to stop HiQ by using, among other things, the Computer Fraud and Abuse Act (CFAA), which is a federal cybersecurity and anti-hacking law. In basic terms, the CFAA says that a computer may not be accessed without authorization or in excess of authorization.

The profile data on LinkedIn was and is public. But LinkedIn didn’t like HiQ scraping its content and issued a cease-and-desist order in 2017. The letter stated that HiQ was in violation of LinkedIn’s user agreement as well as California and federal law, including the CFAA among others. LinkedIn also said that it would technically block HiQ’s efforts to scrape the site.

HiQ sued for a preliminary injunction against LinkedIn and won at the district court level. The court ordered LinkedIn to allow HiQ access to the content again. LinkedIn appealed to the Ninth Circuit.

Who’s “authorized” to access website content. A central question in the case involved determining, once HiQ received LinkedIn’s cease-and-desist letter, whether it was “without authorization” under CFAA. The Ninth Circuit said no.

CFAA contemplates information that is not publicly accessible (e.g., password protected). Public LinkedIn profiles were not password protected. In simple terms: only if the LinkedIn data was non-public would the company have been able to invoke CFAA to block HiQ’s access.

LinkedIn argued that HiQ violated the terms of its user agreement. The Ninth Circuit pointed out that its status as a “user” was terminated by LinkedIn with the cease-and-desist letter. In addition, LinkedIn didn’t claim any ownership interest in the public profile content. And while LinkedIn also said it was also seeking to protect users’ privacy rights in blocking HiQ, the court didn’t buy that argument regarding public profile information — where there was little or no expectations of privacy.

Other potential ways to block scraping. The case was substantially about CFAA, though there were other claims the court discussed. In the end, it didn’t say a website owner doesn’t have any recourse against wholesale appropriation of its public content. The court said that other laws could apply: “state law trespass to chattels claims may still be available. And other causes of action, such as copyright infringement, misappropriation, unjust enrichment, conversion, breach of contract, or breach of privacy, may also lie.”

The Ninth Circuit didn’t analyze the application of any of these theories to the facts of HiQ, however. It simply said they might apply to protect against scraping or content appropriation.

In response to the decision, a LinkedIn spokesperson offered the following statement: “We’re disappointed in the court’s decision, and we are evaluating our options following this appeal. LinkedIn will continue to fight to protect our members and the information they entrust to LinkedIn.”

Why we should care. This case may not be over and could ultimately wind up before the U.S. Supreme Court. Its broadest interpretation, however, appears to be: any “public” online data not owned or password protected by a publisher — and facts cannot be copyrighted — can be freely captured by third parties.

At the end of the opinion, the court expressed concern about “giving companies like LinkedIn free rein to decide, on any basis, who can collect and use data—data that the companies do not own, that they otherwise make publicly available to viewers, and that the companies themselves collect and use—risks the possible creation of information monopolies that would disserve the public interest.”


This story first appeared on Search Engine Land. For more on search marketing and SEO, click here.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.


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What location data can tell us about the state of Starbucks’ pumpkin spice latte


Greg Sterling

Even though Autumn doesn’t officially start until September 23, Labor Day marks the effective start of the season for most people. School is back in session, the weather starts to turn (a bit) and the much-loved but equally derided pumpkin spice latte (PSL) makes its return.

Been around now for 15 years. The flavored coffee drink was initially introduced by Starbucks in 2003 and has now been in the market for 15 years. It has almost single-handedly inspired an entire sub-genre of seasonal foods.

Grocery store display of pumpkin-spiced foods

During its early years, the novelty of the coffee drink brought in new customers regularly. And while it has become seasonal staple of many people’s caffeinated beverage routines, its impact on Starbucks sales and store visitation appears to waning.

Pumpkin-spice fatigue? According to a foot traffic analysis by location intelligence company Gravy Analytics, the venerable yet caloric drink didn’t drive additional any incremental visits when it was re-introduced in 2018. Gravy observed, “Average daily foot traffic decreased by 2%. Starbucks customers also didn’t visit their local Starbucks more frequently once the pumpkin spice latte was released. Average daily visits per device remained flat throughout the period.”

It’s not clear whether the public has become indifferent to the Starbucks drink in particular or whether there’s growing pumpkin-spice fatigue (PSF) more generally. Based on Starbucks’ foot traffic data, Gravy speculates that competing chains, such as Dunkin, may not reap rewards they anticipate from their own pumpkin spice drinks.

Starbucks Foot Traffic by Day of Week (Jul 15 – Oct 13, 2018)

Source: Gravy Analytics (2019)

Conversely, Gravy previously showed that the introduction of the meatless Impossible Burger drove a nearly 20% increase in visitation to participating Burger King stores in test markets. This (and sales data) prompted the chain to introduce the faux burger nationally last month.

Why we should care. Location data has many uses. Audience segmentation and offline attribution are the most common. Competitive insights are gaining currency as well. But another important use case is product testing. Location data can be used a tool to determine the impact of a fast-food menu item, in this case, on store visits before the broader introduction of the product.

The pumpkin-spice latte is a lighthearted example to prove a larger point about the utility of location data to provide customer insights. And while test marketing and sales data have historically been used to determine product viability, location data can help assess whether that product still has market appeal — or has run its course.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.


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Pulling back the curtain on location intelligence


Greg Sterling

There are perhaps 20 companies offering location data or location analytics. X-Mode is less well-known than many others but says it’s one of the few, primary sources of “first party” location data in the market. We caught up with Josh Anton, founder and CEO of X-Mode, to get his take on the current state of location intelligence, what marketers need to look for in a data partner and some of the changes coming with stricter data-privacy rules.

ML: What does X-Mode do?

JA: X-Mode was founded by the people behind the widely popular campus
safety app Drunk Mode. We work with app developers and data buyers to offer the
highest quality location data that meets all current regulatory standards
including the GDPR and CCPA.

has one of the most accurate location data panels in the industry and receives
the majority of its data directly from mobile app publishers through XDK, its
proprietary location-based SDK. With over 300 apps on its platform, X-Mode
licenses a high accuracy (70% accurate within 20 meters), dense data panel that
includes mobility metrics (speed, bearing, altitude, vertical accuracy), near
real-time GPS, and other detection capabilities (IoT, Wi-Fi, and Beacon).

provides this anonymized user panel to hundreds of clients across multiple
industries including Mapping and Location Services, AdTech, MarTech, FinTech,
Smart Cities, Real Estate and InsurTech.

ML: What was Drunk Mode and how did it evolve into

JA: Drunk Mode was the living map for
when you went out partying. Drunk Mode stopped you from drunk dialing your
friends, allowed you to find your drunk friends, and showed you where you went
last night. A lot of our focus was how we leverage location to make the college
student’s night a bit safer.

To continue start generating revenue Drunk Mode
began monetizing location data in 2015, as display advertising opportunities
were limited and low value. During this time our team saw two major
opportunities for disruption in the location data industry: 1) data licensees’
need for high-quality location data and 2) publishers looking for incremental
monetization. Due to Drunk Mode’s investment in accurate location technology
for college safety (breadcrumbs), we already had established contracts
monetizing location and understood the pain points of having users opt-in to
sharing location. We were in a unique position to solve numerous issues and
generate a “win-win-win” for publishers-consumers-X-Mode.

Thus, the X-Mode Location Data Network was born in
Q2 2017. We leveraged our new XDK 1.0 that was built off the core underlying
technology of our Drunk Mode application and now powers X-Mode’s location
platform. Having grown our network to 65M+ global users in less than 2 years,
we realized early on that location-based use cases we built around Drunk Mode
had a much larger impact than we ever imagined.

Instead of creating a network around college safety,
we can now help optimize emergency routes. Rather than just offering drunk food
discounts to users after a long night out, we can now power fortune 500
companies’ ability to better optimize their ad-spend to target around location-based
moments at scale. In the past, we gave Uber/Lyft discounts to help college
students get home safely, and now at X-Mode have the power to help optimize
transportation routes for the masses. We realized there was a much bigger world
outside college and Drunk Mode sobered up to what people know as X-Mode today.

ML: You made the statement that X-Mode was one of a small
number of “first party” location-data providers in the U.S. You also suggested
there’s only a finite supply of available location data in the market. Please

JA: If a location company wants to build an audience or measurement product focused in the U.S. that their end clients use, that company would typically need to combine bid-stream data, low-quality aggregator data, their own always-on SDK data and/or first-party SDK companies. They would need to get to 30M DAUs/75M MAUs for measurement and 30M DAUs/250M MAUs for audience retargeting.

Even if one combines the top three companies in the location space, 70% of the true first-party data in the market (from an “always-on” location SDK), you only see ~30M DAUs in the U.S. (accounting for overlap). If you go downstream, there are only about 5,000 apps with over 2,000 DAUs that have appropriate permissions to run “always-on” location, with about 40% of that number monetizing location.

The reason why it seems like there is an infinite supply of location data in the market is because there’s still a huge number of companies taking low-fidelity data from ad-based SDKs (bid-stream) and creating derivative products to achieve artificial scale. This approach isn’t useful for measurement. Even worse, this approach does not have the privacy permissions needed to navigate a privacy conscious world.

Almost every location intelligence company has some
sort of SDK. However, the real questions that people should be asking when it
comes to understanding location data licensing are the following: 

  1. What percentage of users come from first-party SDK data vs. bid-stream or aggregated ad-based SDK data? Can you name the suppliers that make up your feed under a non-solicitation?  Most importantly, how do you really know it’s coming from an SDK?
  2. Do you know whether this data is coming directly from an app and not just recycled data from another 3rd party? Ask for the app categories and redacted screenshots of some of the larger apps’ privacy policies under a non-solicitation.
  3. Is the data being collected directly from an app? Ask questions about collection methodology; a clean panel will have a pretty standard methodology across the board.

The best panels on the market for measurement or audiences will have 60%+ of their data sourced from their own SDK or from other first-party SDK companies like X-Mode. However due to economics, and buyers not realizing that there are only a handful of companies that control first-party data, companies default to building their data products off of low-fidelity, low-cost data. Companies buying location data often think of it as a commodity, without thinking about data quality and privacy implications, which will occur in the coming months as it becomes much harder to sell data where neither the publisher nor users know their data is being monetized.

ML: You said 60% or 70% of X-Mode data has 20-meter (or better)
accuracy. How is that accomplished?

JA: We use high-accuracy GPS settings at
a specific cadence and machine learning to understand when the best time to
trigger location may be, around a visit/movement. Then we layer beacon
trilateration to enhance our collection methodology, which helps when mapping
locations in a mall or a dense city block.

ML: Many companies get location from the bid-stream but claim to clean it up and discard inaccurate data. Are you skeptical? And what role, if any, does bid-stream location data have to play in the ecosystem?

JA: I am skeptical because there are actually two issues with bid-stream data. The first is data accuracy (already discussed). The second is a lack of persistent collection. With bid-stream data, you are only capturing location when someone views an ad. It’s limited to online behavior.

ML: What impact do you believe CCPA will have on location data, in terms of its availability and quality?

JA: Right now, there is a lot of fluff in
the market. Only three main first-party suppliers of location data in the USA
(X-Mode, Cuebiq and Foursquare) control 70% of the first party supply of
background location in the market. These companies not only work with
publishers directly, but also have a quality SDK and control the relationship
with the publisher to pop-up the proper opt-ins needed to navigate CCPA or the
other 30+ states that are passing some sort of legislation requiring explicit

Third-party aggregators out there, getting data
either through ad-based SDKs (where publishers may not know their data is being
monetized) or through the bid-stream, will have issues not only sourcing data
at scale, but also providing that data with the proper consent mechanisms
needed by agencies and brands.

Privacy is a good thing because it gives consumers more control over their data. At the same time wipes out a lot of the “fluff data” in the market coming from 3rd party aggregators. Companies building location-based solutions will have to rely on first-party SDK data companies like X-Mode, Cuebiq, and Foursquare to power their solutions so they can stay on top of privacy and control quality. In the next 18 months, I expect to see both consolidation of first-party SDK players like ourselves and folks that are low quality aggregators to pivot or evolve into analytics or other location-based tools upstream.

ML: What are the most important things brands and
marketers need to understand about working with location data?

JA: The most important two things brands and marketers need to ask
themselves when looking at targeting and attribution are: 


  • How did you calculate a visit and dwell time?
  • How was the data sourced to create this visit/dwell time and how confident are you about each visit/dwell time? What filters do you have in place for outliers (i.e., what was the cadence of collection, filters for speed when someone’s driving, etc.)?
  • What is the average number days seen across your panel (i.e., DAU to MAU Ratio)? 2+ weeks is the gold standard but anything above 5+ days is not bad.
  • In terms of how you map location data to a visit, what’s the high-level black box that you used to do this (i.e., polygon, check-ins, point radius, etc.)? Polygons and check-ins are going to be much more accurate than point radius, which is what most companies use today. Foursquare and Safegraph were ahead of the game here.

Transparency and privacy:

  • Where was this data sourced and how was it collected: server to server vs. SDK vs. directly from an app?
  • How are you determining or mandating you have the legal right to use this data for your defined use-case — that is: the contract terms and privacy policies of some of the larger contributors to your panel?

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.


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Don’t call me: Nearly 90% of customers won’t answer the phone anymore [Study]


Greg Sterling

There’s an ongoing debate about the role of telephone sales and whether they’re effective anymore. Many pundits have long asserted that “cold calling is dead,” but is any form of outcalling or inside sales effective now?

Declining success rates. A new survey and report from Zipwhip (registration required), intended to promote messaging, argues the phone as a channel is experiencing decreasing effectiveness for multiple reasons. Indeed, plenty of anecdotal evidence indicates reaching prospects over the phone is a growing problem across markets, whether the targets are consumers or b2b buyers.

Widely cited data from separate studies argue that fewer than 2% of cold calls result in meetings and that cold calling is ineffective more than 90% of the time. But these statistics are from old studies that don’t appear to be available anymore, only the passing third-party citations. Yet these assertions appear to support anecdotal experience.

Conversely, there are some who still argue that cold calling can be successful if done properly.

87% mostly ignore calls. The Zipwhip survey (n=520 U.S. adults) found that 87% of respondents said they ignore phone calls from unknown numbers “often” or “very often.”

How often do you ignore/reject phone calls from businesses and unknown numbers?

Source: Zipwhip consumer survey (2019)

This is undoubtedly driven by the increase in robo calls and mobile-phone spam, which First Orion has said will represent about 45% of mobile calls in the U.S. this year. This rise in spam is leading to various anti-call-spam solutions and just plain call avoidance by consumers. Indeed, the top piece of advice from the FCC to combat mobile phone spam is: “Don’t answer calls from unknown numbers. If you answer such a call, hang up immediately.”

The Zipwhip study goes on to explore the various reasons people don’t want to answer the phone. Among them, people are too busy, calls are intrusive or they prefer to communicate in other ways.

Select why you avoid phone calls from businesses/unknown numbers (select all that apply)

Source: Zipwhip consumer survey (2019)

Only 4% don’t think calls disruptive. Beyond this, the survey asked “how often do you find calls to be disruptive?” Respondents said:

  • Always — 27.69%
  • Sometimes — 68.5%
  • Never — 3.65%

In other words, less than 4% were generally open to receiving phone calls.

None of this should be interpreted to suggest that overall call volumes are declining. Indeed, (legitimate) call volumes are growing according to call tracking companies and several studies. BrightLocal, for example, found that the phone was the preferred channel for consumers to contact local businesses. And a recent survey from Broadly found that a majority of small businesses see the phone as their most important channel.

Why we should care. There’s an overall sense that tried-and-true sales channels (e.g., email) are declining in effectiveness. As the data above show, this is also true for calls — when they’re unsolicited. While some stubborn sales executives might say cold calls have a role to play, the evidence argues this approach is getting less efficient and more expensive over time.

One response (now almost a cliche) is that in-bound marketing is the answer and dramatically improves telephone close rates. But as most marketers already well understand, brands need to diversify their prospecting and communications strategies to reach audiences through the channels they prefer. Taking pressure off the phone enables it to become much more effective in this “don’t call me” era.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes a personal blog, Screenwerk, about connecting the dots between digital media and real-world consumer behavior. He is also VP of Strategy and Insights for the Local Search Association. Follow him on Twitter or find him at Google+.


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inMarket acquires rival Thinknear, suggesting consolidation ahead for location intelligence


Greg Sterling

Location-based ad platform inMarket is buying Thinknear from owner Telenav. Thinknear is a location-based ads and analytics provider that competes with numerous other companies in the segment.

Thinknear a non-core asset. Telenav is a connected car, navigation and fleet management platform. The transfer of Telenav to inMarket received a quick mention in Telenav’s earnings release yesterday and zero discussion on the company’s earnings call, suggesting its ads business was a tiny fraction of revenue. Telenav is thus likely shedding the ads unit to focus on its core, connected cars business.

The acquisition, following Foursquare’s earlier purchase of Placed from Snap in May, suggests that more consolidation may be ahead for the segment. The value of the deal was not disclosed; however, Telenav will gain a minority equity stake in inMarket. The transaction will close at the end of September.

Too many companies that sound the same. Many companies in the location intelligence segment began life selling media but later moved into selling data and analytics exclusively. Telenav and inMarket continue to sell location-targeted media. Early on, inMarket emphasized digital-to-store analytics and in-store marketing but has broadened its offering considerably in the past five years. The company works with a mix of first and third-party data.

There are at least 20 companies that make similar-sounding claims about using mobile-location data to target audiences and measure the offline impact of media (digital and traditional), store visitation and sometimes sales. A partial list includes Foursquare/Placed, PlaceIQ, Factual, Ubimo, Cuebiq, Blis, Skyhook, GroundTruth, Verve, Unacast, Reveal Mobile, NinthDecimal, HERE, Spatially, Pitney Bowes, Gravy, X-Mode, UberMedia and others.

Google and Facebook offer similar targeting and analytics capabilities.

A potential data reckoning ahead. The coming of the California Consumer Privacy Act (CCPA) next year may put pressure on some of these companies as third party location data becomes potentially less available and mobile operating systems give consumers more control over who can access location and how often. However, the precise impact of CCPA on location data throughout the broader programmatic ecosystem remains to be seen.

There are also wild cards such as New York’s proposed law substantially banning the transfer of location data collected within the city to third parties. Other municipalities may follow and introduce similar legislation.

Therefore, expect companies that have their own “first-party data” (via developer SDKs) to be near-term acquisition targets.

Why we should care. Putting aside the issue of data privacy (a major one), all brands and enterprise marketers should be working with location data for audience segmentation, business intelligence insights and media measurement. Unless you’re a pure e-commerce company this data is the only way to get a clear and complete picture of media efficacy and the buyer’s journey. Location data can also be utilized as the centerpiece of multi-touch attribution.

For questions to ask location intelligence companies before deciding how to proceed see How to choose a location data provider.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes a personal blog, Screenwerk, about connecting the dots between digital media and real-world consumer behavior. He is also VP of Strategy and Insights for the Local Search Association. Follow him on Twitter or find him at Google+.


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Proposed NYC law would ban sharing of location data within the city


Greg Sterling

Third party data is increasingly under threat. As one case-in-point, a bill introduced this week would amend the New York City administrative code to prohibit the transfer or sharing of consumer location data with third parties within city limits.

In other words, the party that collects or captures the data, even with opt-in consent or not, could not share it with another entity. It appears to be a very bright line.

Would not impact first parties. The proposed law would not eliminate use of location for ad targeting and offline attribution; first party platforms and publishers could still do these things. But it would impact data brokers, MarTech platforms, agencies and the programmatic ecosystem, which relies on the free flow of third party data.

The bill is explicitly directed at telecom companies and mobile apps that capture or have access to user location. It’s designed to protect consumers who may not be aware their location data is being shared. But this law would appear to not make an exception for opt-in consent to sharing.

Each violation worth $1,000. Violations would bring $1,000 in penalties per incident, up to a maximum of $10,000 per day. New York City’s Department of Information Technology would enforce the law but individuals would also have a right to sue and collect damages.

The bill provides for a number of exceptions, including for selected law enforcement use cases and for other first responders. It would take effect 120 days after being signed into law.

Passage not guaranteed. The bill still faces a number of hurdles and its passage is not a forgone conclusion. Technology and advertising interests will probably seek to block or dilute the bill before passage. And even if passed, it would almost certainly face legal challenges. But the genie is out of the bottle. We may see similar rules proposed in cities — and potentially states — across the country in the coming months.

Google and Facebook won’t be impacted. Google and Facebook would not be affected because they can collect and use location data for targeting and attribution within the closed environments of their platforms. They are first parties.

Just as they have not really be harmed by GDPR, Google and Facebook would fare better than other entities that rely on the third party data ecosystem. Indeed, programmatic ad networks would probably be prevented from targeting ads any more precisely than New York City. It’s unclear if even that level of user location targeting would be allowed.

Why we should care. Assuming the law passes, there are some unanswered questions. Among them, will advertisers or agencies (or tools used by agencies) be blocked from accessing location data regardless of the ad platform? In other words, Google and Facebook could use location but would reporting that out to customers violate the law?

The more local and state rules there are that seek to govern privacy and data security the more these jurisdictions make the case for a uniform federal law and preemption. Paradoxically, these local laws are appearing precisely because there’s no new privacy rules at a national level. And it’s unlikely we’ll see any before the 2020 elections.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes a personal blog, Screenwerk, about connecting the dots between digital media and real-world consumer behavior. He is also VP of Strategy and Insights for the Local Search Association. Follow him on Twitter or find him at Google+.


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Survey finds 89% of marketers seeing increased sales using location data


Greg Sterling

Last year, Lawless Research and Factual found 87% of marketers were using location data or targeting in their marketing campaigns. A new follow-up survey showed comparable usage but also improved results, including increased sales (89%) customer growth (86%) and higher customer engagement (84%).

The 2019 survey consisted of 700 U.S. based mobile marketers drawn from a B2B survey panel and included 536 consumer brands and 164 agencies.

Have you experienced the following benefits from using location-based marketing and/or advertising?

Source: Lawless Research/Factual (2019)

Only 24% doing offline attribution. More than 9 in 10 surveyed marketers plan to use location data in the future. However, strangely, only 24% are using or plan to use it for store visitation or offline measurement. According to the report, “The primary use of location data is for targeting (67%) and 52% use location data for audience engagement, campaign strategy and customer experience or personalization.”

It’s mysterious why more aren’t using offline attribution, but the report and the survey don’t explore that question. And if 89% are seeing increased sales from use of location, how is that being tracked? (Possibly by matching first party transaction data with ad exposures.) However, these 700 marketers are not all driving e-commerce transactions.

How do you currently use (or plan to use) location data in your campaigns?

Source: Lawless Research/Factual (2019)

Mobile is the main channel currently seeing use of location data (81%). However the survey found that marketers plan to use it in other channels: advanced TV (49%), digital out-of-home (47%), smart speakers (45%) and automotive (28%), which is not itself a channel. More than an exact representation of where it will be deployed, these findings indicate the market sees location as a versatile tool for use in many contexts.

Site traffic still top KPI. Another very interesting finding concerns measurement. Most of these marketers are using traffic to their websites as the principal measure of campaign effectiveness. I would see this as a general statement about all campaigns and not just those involving location data.

With the exception of “purchases or sales,” “sales lift,” “attribution modeling” and “in-store visits,” these are either brand metrics or “proxy metrics” and not tangible business outcomes. This would seem to reflect a general lack of measurement sophistication, given the available tools.

Which of the following do you use to measure digital advertising effectiveness?    

Source: Lawless Research/Factual (2019) 

Quality and accuracy are the top considerations for these marketers in working with location data partners. On this point marketers are becoming more sophisticated and increasingly interested (62%) in looking behind the curtain to understand how the data is being collected.

Why we should care. This report shows the mainstreaming of location as a horizontal tool for audience segmentation and targeting across channels and categories. However, there’s still a long way to go, it appears, when it comes to measurement. The low location-attribution figure (24%) is very surprising and somewhat inconsistent with anecdotal conversations I’ve had with other data providers and platforms.

Another issue not fully discussed in the report, privacy compliance, will be increasingly important when using location data. CCPA, which takes effect next year, could significantly impact the ability of marketers to use third party location data in their campaigns.

About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes a personal blog, Screenwerk, about connecting the dots between digital media and real-world consumer behavior. He is also VP of Strategy and Insights for the Local Search Association. Follow him on Twitter or find him at Google+.


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