Top 10 Influencer Brands

 

Study finds the Ritz's influencers in March had highest proportion of fake followers.
Study finds the Ritz’s influencers in March had highest proportion of fake followers. Credit: Ritz-Carlton

Procter & Gamble Co. has been vigorously rooting out fraud and unverified data from its digital buys while also doing more influencer marketing, but those two things may be at cross purposes. In a new study, two P&G brands last month ranked among the top 10 in using paid influencers with fake followers.

The data, which comes from Points North Group (March 2018), shows that Pampers and Olay ranked No. 4 and 10, respectively, on the list of brands with the most fake followers among their paid influencers last month; Pampers with 32 percent and Olay with 19 percenty. Topping the study’s list: Ritz-Carlton, with a whopping 78 percent of fake followers for its influencers.

Ritz-Carlton didn’t respond to requests for comment. P&G spokeswoman Tressie Rose declined to comment on report specifics, since the company hasn’t seen the data and isn’t familiar with Points North or its methodology. “There are a lot of companies out ther offering services to combat this,” she says. “Bot fraud is an industry-wide issue and one we’re continuing to actively work on.”

Even as use of influencer marketing by big marketers grows, so do questions about how it’s measured. Reach numbers used to measure influencer campaigns often come from raw follower counts, without regard to how many followers actually saw posts—or were real.

Numbers marketers usually get on influencer campaigns come either from their influencers or third-party providers “grading their own homework,” as Points North co-founder Peter Storck sees it. He’s now working with clients, whom he says he doesn’t yet have approval to name, to help “get real measures of their influencer marketing, because they don’t get them from the partners they work with.”

Points North is a firm founded by former executives with analytics experience going back to the old Jupiter Research digital ad measurement business, as well as with the Word of Mouth Marketing Association (now part of the Association of National Advertisers) and such influencer networks as CrowdTap and House Party. Storck’s joined co-founder Sean Spielberg, who was with Crowdtap, to form what Storck calls “the Nielsen of influencer marketing.”

Storck says he’s unaware of any other third-party audience measurement dedicated to influencers space, though some firms have sought out third-party validation of their reach numbers other ways. Cincinnati-based Ahalogy, for example, only charges clients for digital impressions verified by Oracle’s Moat on content created by its influencers.

Points North is releasing its first public data in the form of lists of the biggest spenders on influencer marketing in March, the most efficient spenders based on cost per thousand impressions (CPM), and those with the most fake followers. Storck says work for private clients has included a large cosmetics brand where $600,000 out of a $2 million outlay for influencers was for impressions that weren’t seen or were seen by fake followers.

The spending data is based on analysis of influencers used by brands and industry norms on payments, which Points North founders say average 0.3 cents per follower per post across the industry based on their prior sell-side experience and more recent input from clients. It’s an estimate, but one they say they’re looking to apply consistently.

Fake follower counts are based on Points North scanning followers of influencers to sort out such things as accounts making comments in languages that don’t make sense for the content or the influencer, or accounts making the exact same comments across multiple influencers and posts. Storck says the algorithm is similar to what e-mail users lean on to sort out spam.

The CPMs are based on the spending estimates and effective reach, which not only subtracts fake followers, but also uses estimates of how many legitimate followers actually see posts, leaning on engagement rates for posts and norms for viewership gleaned from actual influencers, who get such information from their own Instagram business accounts, for example.

The top influencer spenders last month, as estimated by Points North, include names you’ve likely heard of, such as Amazon, Walmart and Mercedes Benz, but also the more obscure—at least until that influencer spending kicks in—like Flat Tummy, Waist Gang Society and SugarBearHair vitamins.

Among the most efficient spenders was Heinz Ketchup, owned by the Kraft Heinz and the ever-thrifty 3G Capital; Ulta Beauty; and Clorox Co.‘s Hidden Valley, all with CPMs around $2 or less.

P&G also had a brand on the top 10 most efficient, Vicks.

Below, top spenders, most efficient, and most fake followers.

Top Influencer Marketing Spenders on Instagram

Points North Group (March 2018)

Rank Advertiser Estimated Spend
1 Flat Tummy Co $1,560,178
2 Amazon $646,212
3 Mercedes-Benz $515,697
4 Land O’Lakes $455,586
5 Stella Artois $423,175
6 Walmart $329,957
7 Waist Gang Society $317,783
8 SugarBearHair $316,182
9 Freeform $304,357
10 Calvin Klein $250,763

Most Efficient

Brands Achieving Lowest Effective CPMs for Instagram Sponsored Posts (>$10k Spend) in

Points North Group (March 2018)

Rank Advertiser CPM
1 Heinz Ketchup $1.78
2 Ulta Beauty $2.02
3 Hidden Valley $2.11
4 SuspiciouS Antwerp $2.13
5 Marc Jacobs Beauty $2.56
6 Chloé $2.97
7 Vicks $3.09
8 Call of Duty $3.12
9 Justice $3.16
10 BioClarity $3.19

Most Fake Followers

Points North Group (March 2018)

Rank Advertiser % Fake Followers
1 Ritz-Carlton 78%
2 Aquaphor 52%
3 L’Occitane 39%
4 Pampers 32%
5 DSW 29%
6 Crocs 25%
7 Lulus 22%
8 Neiman Marcus 22%
9 Magnum Ice Cream 20%
10 Olay 19%
Advertisements

Getting a sharper picture of social media’s influence

New research shows that buzz plays a greater role than previously thought in getting consumers to buy and that the pool of the most effective influencers is largely untapped.

Over the past decade, marketers have increasingly turned to social-media networks like Facebook and Twitter to create buzz around their products. But what impact do tweets and other recommendations have on sales, and how can companies get a bigger return on their investments in these important channels?

To get a clearer view, we examined the purchase decisions of 20,000 European consumers, across 30 product areas and more than 100 brands, in 2013 and 2014. Respondents were asked how significantly social media influenced their decision journeys and about instances when they themselves recommended products.1 The research compiled social and demographic information, as well as data on social interactions on Facebook, Twitter, and other social networks. The data gathered cover a range of decision-journey touch points leading up to purchases, as well as social activities after purchase. We found that the impact of social media on buying decisions is greater than previously estimated and growing fast, but that its influence varies significantly across product categories. Moreover, only a small slice of social influencers are creating the buzz.

A growing importance

Social recommendations induced an average of 26 percent of purchases across all product categories, according to our data. That’s substantially higher than the 10 to 15 percent others have estimated.2 SeeConnected Marketing: The Viral, Buzz and Word of Mouth Revolution, edited by Justin Kirby and Paul Marsden, Oxford, UK: Butterworth-Heinemann, 2006. For the 30 product categories we studied, roughly two-thirds of the impact was direct; that is, recommendations played a critical role at the point of purchase. The remaining third was indirect: social media had an effect at earlier decision-journey touch points—for example, when a recommendation created initial awareness of a product or interactions with friends or other influencers helped consumers to compare product attributes or to evaluate higher-value features. We found that in 2014, consumers made 10 percent more purchases on the back of social-media recommendations than they had in 2013.

Nuances are essential

Consumers, we found, access social media to very different degrees in different product categories. At the low end, only about 15 percent of our respondents reported using social media in choosing utility services. For other categories, such as travel, investment services, and over-the-counter drugs, 40 to 50 percent of consumers looked to social recommendations.

Product categories tend to have their own discrete groups of influencers. Our data showed that the overlap of recommenders between any two consumer categories was very small—a maximum of 15 percent for any two pairs of products we analyzed. Timing matters as well: a first-time purchaser, for example, is roughly 50 percent more likely to turn to social media than a repeat buyer.

While the role of digital influence is expanding, the analog world remains important. Among the more than 100 brands we studied, about half of the recommendations were made offline—in person or by phone. Offline conversations were up to 40 percent more likely than digital interactions to influence purchase decisions of products such as insurance or utilities.

Power influencers and the long tail

Our research shows that a small number of active influencers accounted for a disproportionate share of total recommendations (exhibit). These power users are even more significant for product categories such as shoes and clothing: 5 percent of the recommenders accounted for 45 percent of the social influence generated.

Exhibit

Navigating in a changing environment

As companies look to maximize returns from their social strategies, they can both encourage would-be customers to engage in more social interactions and inspire more influencers to express enthusiasm for their products.

On the demand side, our research suggests that online articles written by journalists prompt consumers to seek out social media to further inform purchases (and that public-relations spending to generate such articles may be a worthwhile investment). Consumers who use search engines to gain some initial knowledge of a product are also more likely to tune in to social media before a purchase. Companies that spend effectively on search-engine optimization (to move their product mentions to the top of search results) can expect to benefit from a greater social-media impact, as well.

Television advertising, by contrast, tends to act as a substitute for social media rather than complementing it. Relatively few customers were prompted to seek out social influences after viewing a TV spot.3 Interestingly, this contrasts with consumers’ use of social media to comment on TV-show episodes. See “Living social: How second screens are helping TV make fans,” Nielsen, August 4, 2014, nielsen.com.

On the supply side, prompting the long tail of less active influencers may require creativity and a greater use of data analytics. Our research found, paradoxically, that if companies allowed endorsements only, they generated a less strong response than companies that invited any sort of comment. Positive remarks were three times more numerous than negative ones, and some companies demonstrated that they could turn negative vibes to their advantage by responding quickly.

Other companies are amplifying positive noise by making the recommenders’ data “speak.” Through machine learning and the application of advanced analytics to recommenders’ profiles, they obtain a granular understanding of product preferences and purchasing behavior. That analysis becomes a key input into sophisticated recommendation engines that identify potential customers and send them messages such as “purchasers like you bought this appliance” at key points along the decision journey. These engines are highly effective at converting customers,4 Others have estimated that these engines are responsible for more than 50 percent of purchases or viewer activity at digital leaders such as Amazon and Netflix. See JP Mangalindan, “Amazon’s recommendation secret,” Fortune, July 30, 2012, fortune.com; and Tom Vanderbilt, “The science behind the Netflix algorithms that decide what you’ll watch next,” Wired, August 7, 2013, wired.com. though with an important caveat: the influence the engines generate can be as much as 75 percent lower if messages aren’t highly personalized and targeted.

The pathways of social influence are shifting constantly. Looking ahead, better mobile devices and more robust social applications will make it even easier to share experiences about products and services. Companies can’t afford to fall behind this powerful curve.

About the author

Jacques Bughin is a director in McKinsey’s Brussels office.

 

McKinsey: The strength of ‘weak signals’

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Snippets of information, often hidden in social-media streams, offer companies a valuable new tool for staying ahead.
February 2014 | byMartin Harrysson, Estelle Métayer, and Hugo Sarrazin

As information thunders through the digital economy, it’s easy to miss valuable “weak signals” often hidden amid the noise. Arising primarily from social media, they represent snippets—not streams—of information and can help companies to figure out what customers want and to spot looming industry and market disruptions before competitors do. Sometimes, companies notice them during data-analytics number-crunching exercises. Or employees who apply methods more akin to art than to science might spot them and then do some further number crunching to test anomalies they’re seeing or hypotheses the signals suggest. In any case, companies are just beginning to recognize and capture their value. Here are a few principles that companies can follow to grasp and harness the power of weak signals.
Engaging at the top

For starters, given the fluid nature of the insights that surface, it’s often useful to get senior leaders actively involved with the social-media sources that give rise to weak signals. Executives who are curious and attuned to the themes emerging from social media are more likely to spot such insights.1 For example, a global manufacturer whose high quality and low prices were the topic of one customer’s recent social-media post almost certainly would not have examined it but for a senior executive who was a sensitive social “listener” and found its implications intriguing. Did the company have an opportunity, the executive wondered, to increase prices or perhaps to seek market share more aggressively at the current prices?

To find out, the executive commissioned research to quantify what had started out as a qualitative hunch. Ultimately, the low-price perception turned out to be an anomaly, but the outsize perception of the product’s quality was widely held. In response, the company has started funneling marketing resources to the product in hopes of building its market share by capitalizing on its quality and differentiating it further from the offerings of competitors.
Listening and mapping

As the manufacturer’s example implies, spotting weak signals is more likely when companies can marshal dispersed networks of people who have a deep understanding of the business and act as listening posts. One global beverage company is considering including social-media awareness in its hiring criteria for some managers, to build its network and free its management team from “well-rehearsed habits.”

Weak signals are everywhere, of course, so deciding when and where to keep the antennae out is critical. One such situation involves a product, market, or service that doesn’t yet exist—but could. Consider the case of a global advertising company that was investigating (for one of its clients) a US growth opportunity related to child care. Because no one was offering the proposed service, keyword searches on social media (and on the web more broadly) wouldn’t work. Instead, the company looked to social-media platforms where it might find weak signals—finally discovering an online content service that allows users to create and share individualized newspapers.

In the child-care arena, digital-content channels are often curated by mothers and fathers, who invite conversations about their experiences and concerns, as well as assemble relevant articles by experts or government sources. Analysts used semantic clues to follow hundreds of fine-grained conversations on these sites. The exercise produced a wealth of relevant information about the types of services available in individual markets, the specific levels of service that parents sought, the prices they were willing to pay, the child-care options companies already sponsored, the strength of local providers (potential competitors), and the people in various communities who might become ambassadors for a new service. This wasn’t a number-crunching exercise; instead, it took an anthropological view of local child care—a mosaic formed from shards of information found only on social media. In the end, the weak signals helped the company to define the parameters of a not-yet-existing service.
Spotting visual clues

It’s also useful to search for weak signals when customers start engaging with products or services in new, tech-enabled ways, often simply by sharing perceptions about a company’s offerings and how they are using them. This can be hard for companies to relate to at first, as it’s quite removed from the usual practice of finding data patterns, clustering, and eliminating statistical noise. Spotting weak signals in such circumstances requires managers and employees to have the time and space to surf blogs or seek inspiration through services such as Tumblr or Instagram.

As intangible as these techniques may sound, they can deliver tangible results. US retailer Nordstrom, for example, took an early interest in the possibilities of Pinterest, the digital-scrapbooking site where users “pin” images they like on virtual boards and share them with a larger community. Displayed on Pinterest, the retailer’s products generate significant interest: the company currently has more than four million followers on the site.

Spotting an opportunity to share this online engagement with in-store shoppers, the company recently started displaying popular Pinterest items in two of its Seattle-area stores. When early results were encouraging, Nordstrom began rolling out the test more broadly to capitalize on the site’s appeal to customers as the “world’s largest ‘wish list,’” in the words of one executive.2 The retailer continues to look for more ways to match other customer interactions on Pinterest with its products. Local salespeople already use an in-store app to match items popular on Pinterest with items in the retailer’s inventory. As the “spotting” ability of companies in other industries matures, we expect visual tools such as Pinterest to be increasingly useful in detecting and capitalizing on weak signals.
Crossing functions

As the Nordstrom example demonstrates, listening for weak signals isn’t enough—companies must channel what’s been learned to the appropriate part of the organization so the findings can influence product development and other operational activities. Interestingly, TomTom, a company that offers products and services for navigation and traffic, found that the mechanism for spotting weak signals proved useful in enhancing its product-development process.

As part of normal operations, TomTom monitored social media closely, mining conversations to feed into performance metrics for marketing and customer-service executives. The normal process changed after an attentive company analyst noted that users posting on a UK forum were focused on connectivity problems. Rather than let the tenuous comments get lost in the company’s performance statistics, he channeled them to product-development teams. To resolve the issue, the teams worked directly—and in real time—with customers. That helped short-circuit an otherwise costly process, which would have required drivers using TomTom’s offerings to check out connectivity issues in a number of locales. The broader payoff came in the form of new R&D and product-development processes: TomTom now taps directly into its driving community for ideas on design and product features, as well as to troubleshoot new offerings quickly.

At most companies, weak signals will be unfamiliar territory for senior management, so an up-front investment in leadership time will be needed to clarify the strategic, organizational, and resource implications of new initiatives. The new roles will require people who are comfortable navigating diverse, less corporate sources of information.

Regardless of where companies observe weak signals, the authority to act on them should reside as close to the front lines as possible. Weak signals are strategic enough to demand top-management attention. They are sufficiently important to the day-to-day work of customer-service, technical-development, and marketing teams to make anything other than deep organizational engagement unwise.
About the authors

Martin Harrysson is an associate principal in McKinsey’s Silicon Valley office, where Hugo Sarrazin is a director; Estelle Métayer, an alumnus of the Montréal office, is an adjunct professor at McGill University, in Montréal.

ROI Rankings: Facebook Deemed More Important Than Twitter and LinkedIn, Less Than Google

ROI Rankings: Facebook Deemed More Important Than Twitter and LinkedIn, Less Than Google
September 16, 2013 by MarketingCharts staff

AdAgeRBC-Online-Ad-Platforms-Ranked-by-ROI-Importance-Sept2013 Asked to rank 5 key online advertising platforms by importance in terms of ROI, respondents to a survey conducted by Ad Age and RBC Capital Markets put Google on top, giving it an average rating of 2.1 on a 6-point scale of importance, where 1 is the most important. Google edged out Facebook (average rating of 2.22), from which 9 in 10 respondents are seeing either improved (42.7%) or steady (48.3%) ROI over the past 6 months.
AdAgeRBC-Online-Ad-Platforms-Ranked-by-ROI-Importance-Sept2013
After Facebook, Twitter (average rating of 3.04) was deemed the next-most important for ROI, followed by LinkedIn (3.38), Yahoo (4.23), and AOL (5.6).

Respondents – a mix of marketers of clients (26%), ad agency employees (30%), and media company employees and consultants (44%) – appear to be satisfied with the support provided by Facebook for their advertising efforts. Almost half believe that Facebook’s support for advertisers has improved to some degree over the past 6 months, compared to only 1 in 10 who believe it has to some extent deteriorated. Additionally, roughly three-quarters are very (10.5%) or somewhat (65.2%) satisfied with the data and analytic tracking they receive from Facebook.

Given improving ROI and support, it’s not surprising that advertisers will be increasing their efforts: over the next year, a majority expect to significantly (11.2%) or moderately (44.5%) increase their Facebook advertising budget.

Interestingly, although Facebook is deriving an increasing share of ad revenues from mobile , advertisers don’t see much separation between the ROI of mobile and desktop ads, with a plurality (38%) rating them about the same. Slightly more than one-third feel that mobile ROI is much (7.7%) or somewhat (27.4%) greater, while 26.9% feel the same way about desktop ROI.

There’s more consensus when it comes to Facebook Exchange, used by about 1 in 5 respondents. Of those, two-thirds said it has been somewhat effective for their campaigns, with another 1 in 5 calling it very effective.

About the Data: The survey was conducted in August among 1,200 Ad Age subscribers.

Nielson Report Gauges Companies’ Approach to Advertising on Social Media

NYT Media

Nielson Report Gauges Companies’ Approach to Advertising on Social Media

By TANZINA VEGA

Since the arrival of social media platforms, companies have tried to figure out how to best use them to get their messages to consumers, often with mixed results. Some brands have embraced the notion that social platforms like Twitter allow constant interaction, for better or worse, with their customers.

Others have turned away from some strains of social media, as General Motors did last spring when it stopped advertising on Facebook while raising questions about the return on its investment. The move had a ripple effect in the advertising world, with many brands questioning whether the costs of being on social media were worth it.

A new report issued Tuesday by Nielsen and Vizu, a research company owned by Nielsen, shows that brands think they might be turning a corner, specifically when it comes to paying for their use of social media.The report examined the opinions about social media marketing among more than 500 digital media professionals — including brand marketers, media agencies and advertisers — from September to October 2012.

The study found that that 89 percent of advertisers continued to use free social media products. Nielsen did not release the names of specific social media platforms mentioned by the respondents, but they are likely to include Facebook and Pinterest, as well as Twitter.

Three quarters of the companies surveyed said they were also spending more for social media content, which could include paying bloggers to write posts about a product or using third-party technology to push videos on to the Web in the hope that they become viral.

Seventy percent of the advertisers surveyed said they dedicated up to 10 percent of their budget to paid social media advertising, while 13 percent dedicated more than 21 percent of their budget. Those numbers are expected to increase in 2013.

The results come as companies like Twitter and Facebook are making more diverse advertising options available to brands. Last year, Twitter announced a number of advertising and media initiatives, including a survey product that enables marketers to ask Twitter users a handful of multiple-choice questions. Facebook began testing a new advertising mechanism using a technology called real-time bidding, which allows advertisers to place bids on ad space at specific times.

“Advertisers are starting to look at social media as an integrated part of their advertising strategy,” said Jeff Smith, the senior vice president of product leadership for advertising effectiveness at Nielsen.

Still, companies retained some skepticism about social media strategy, the survey showed. While companies may expect to spend more to market their brands, they also want to be able to quantify the results of their campaigns. A third of the advertisers surveyed said they were unsure about the effectiveness of social media. The same percentage said they were unsure how to measure the return on their investment.

The majority of advertisers surveyed, 42 percent, said they wanted to measure their online campaigns using the same tools they use for offline campaigns, like sales generated and gross ratings points, while adding more measurement tools specific to digital campaigns, including “likes” and click-throughs.

Advertisers are able to tailor ads to specific groups of online users using cookies and other technologies, but they have often relied on whether consumers click on those ads as the main form of measuring how effective those ads have been.

At the Advertising Week gathering last year, Facebook announced that it was moving away from counting clicks as a metric and moving toward a measurement similar to the gross rating point used in television. The company said it was able to tell whether an ad was effective by combining data on when the ad was shown to a user with data about whether products had been sold. The move is meant to help what is known as “brand advertisers,” whose goals may be less tangible than those of direct response advertisers.

A Facebook representative declined to discuss the company’s paid advertising business. Facebook will announce its fourth-quarter earnings on Wednesday.

via Report Gauges Companies’ Approach to Advertising on Social Media – NYTimes.com.