Friday, 28 April 2017

Google launched more than 1,600 new changes in search last year

Google revamped its How Search Works site, the site they launched in 2013 to describe the efforts Google makes in search. Google added some new metrics around the various Google search launches they made last year, how many tests they tried out and the various numbers around their diverse set of search experiments.

Google mentioned the update to this site when they also announced Project Owl earlier this week.

The site shares that Google launched 1,653 new search changes last year, based on 9,800 live traffic experiments, 18,015 side-by-side experiments and 130,336 search quality tests.

As you can see, only a small percentage of what Google tries actually goes live, but to launch over 1,600 new changes in search in a single year is massive. In fact, we don’t know exactly how many of the 1,600 changes are user interface changes versus new feature changes versus algorithmic or ranking changes. I doubt Google would share those details.

What we do know is that only one percent of searchers were part of the 9,800 live traffic experiments and that while we likely covered many of them, I am sure we missed the majority of those experiments.

Here is an animated GIF of the page that documents these numbers:


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Author: Barry Schwartz

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Are you grateful for digital? Part 2: Q&A

Digital Marketing IndustryIn my most recent column, I challenged you to ask if you were grateful for digital. I argued that while marketers claim to be customer-centric, our campaigns rely more on our need to meet sales goals than any objective of the customers.

Well, it got me thinking, do others have similar feelings? Are they grateful for digital? I asked Lynn Wunderman, Director at Pebble Post (my employer), how she feels. Wunderman is a seasoned marketing professional with over 30 years’ experience in direct marketing, database marketing, communications, consulting and general management. Turns out, she has some strong opinions herself, and she shared her insights below:

Q: Are you grateful for digital?

From a data perspective, I find it’s a mixed blessing, and as you touched on in your column, many of my colleagues feel the same way. I am grateful, because all the data we have access to today gives us the potential to make digital marketing really timely and relevant. However, I’m not grateful because there’s just so much data, and it can be difficult to access for supporting meaningful analysis.

We’re literally drowning in data, but starved for knowledge, to paraphrase John Naisbitt. All this data is both a blessing and a curse because making it actionable is such a tremendous challenge.

Q: Customer-centric? Or transaction-centric?

As marketers, we want to be customer-centric — it’s always been our goal. The problem is we’re simply too transactional. We’re often not looking at the bigger picture.

To give you an example, a marketer may use GPS data to determine that a person is near a quick-serve restaurant. Based on that data, the consumer is served an ad featuring an offer for that QSR. Sounds like a smart strategy, right? It is on the surface, but the marketer may have no idea what the potential value of that consumer is. They may be a high-value customer, or they could simply be someone who only visits when they have a deal for a cheap meal — and, in reality, is highly unlikely to ever set foot in that restaurant again without a bribe.

So, that’s not really customer-centric. It’s convenient, I suppose — and opportunistic — but proxies will only get you so far in building a long-term, profitable customer relationship.

The roadblock along our route to customer-centricity is that our approach is not holistic. As marketers, we’re simply not structuring the data in a way that allows us to see the patterns — patterns that could give us the insights we need to market more successfully.

Many veterans of our trade will find this oversight frustrating because in traditional direct marketing, we typically created segments based on the value of our customers. RFM data (recency, frequency and monetary value) was used, and looking back, it may seem rudimentary, but it was effective — largely because it normalized and summarized transactional information across all customers, thus allowing predictive patterns to emerge.

Even in the absence of transactional data, we would use proxies (like scanner panel and syndicated data) to understand and predict who our high-value customers were and where they were in their life cycles. We knew who was worth investing in, and we could avoid attrition by understanding the potential long-term impact of trigger events and making offers that were relevant to where they were in their customer life cycle.

Marketers today have all kinds of data at their fingertips, but they don’t often have or use the tools to harmonize it all and organize it this clearly.

Ultimately, we’re just not being sophisticated enough in our approach to data. We’re limiting our perspective to offers that are specific to what’s happening now, rather than looking at the big picture. We’re grabbing for that low-hanging fruit, and it’s critical to return to that full life cycle view, and the customer’s relationship with the merchant or marketer.

Q: Can we find a way out of the black box?

The tools we use are partly to blame. Black-box programmatic tools and DMPs (data management platforms) are great for predicting the next click, but you lose some nuance along the way. Older tools gave us the opportunity to interpret that data and gain a deeper understanding of segments and audiences. Most platforms and algorithms don’t allow for the learning that helps us understand what entices consumers to inch further along the path to purchase — only that they are moving down the path.

Not knowing that “why” can really stymie the creative process because we lose some understanding of who our audience is. To really be specific in our messaging and build real conversations with these people, we need to understand not just who they are in data points, but what distinguishes them from the broader universe. In other words, it’s not what they have in common with other shoppers that’s important; it’s what’s different about them.

That’s what’s predictive and what moves people up in terms of targeting potential. If you have that information, it feeds the creative process.

And that’s another critical point in this data conundrum: Creative now stands in the shadow of data, when really the two need to share the spotlight. Data can’t do all the heavy lifting in marketing, and marketers must recognize that and invite creative back to the table.

We can use all the data in the world to understand exactly who our target customer is and why they’re there, but we need to bring creative into the process so that we can actually engage them. The art of understanding the customer and how to talk to them seems to have vanished, and in a world where attention spans and digital canvases are getting smaller and smaller, that art is more important than ever.

In conclusion

So, given her perspective shared above, Wunderman’s point is this: Data is important, but it’s not everything — certainly not the way we’re currently using it today. She’s calling for marketers to stop focusing on individual transactions and start focusing more on individuals and what it takes to build long-term relationships and brand advocates.

Maybe if we stop focusing purely on the science of data and spend more time on the art behind the interpretation of data and how it fuels the creative process, we can all start feeling a little bit more grateful for data, and ultimately digital, too.


Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.


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Author: Lewis Gersh

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Google doodle celebrates Marie Harel, the inventor of Camembert cheese

Today’s special Google doodle honors the inventor of the Camembert cheese. Marie Harel was born 256 years ago today in Crouttes, France. She invented the Camembert cheese back in 1791, at the age of 30.

The Google doodle shows the steps it takes to make Camembert cheese in nine different Google logo slides. Google said that the “Doodle celebrates Harel’s 256th birthday with a slideshow that illustrates how Camembert is made, step by step.” “It’s drawn in a charming, nostalgic style reminiscent of early 20th-century French poster artists, such as Hervé Morvan and Raymond Savignac,” they added.

Her work earned her a statue in Vimoutiers in France.

Marie Harel lived to the age of 83 and died on November 9, 1844.

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Author: Barry Schwartz

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The future of local discovery

We’ve entered an exciting time for local marketing. Big Data, digital assistants, augmented reality and beacons will fundamentally change the way users discover locations. As Bob Dylan so aptly pointed out, “The times they are a-changin’.”

As such, local marketers and advertisers need to start thinking about how they’re going to change along with the times. Here’s what you need to know about the future of local discovery.

Big Data: ‘Who’ informs ‘where’

Proximity is the primary ranking factor in local searches. That’s not likely to change. After all, what’s nearby is the fundamental aspect of local discovery.

What is changing, however, is the filter that sorts out, ranks and presents those nearby locations. What filter, you ask?

It’s you.

Going forward, local discovery will function as proximity filtered by your individual preferences. The person searching will inform what locations are shown.

In truth, this is nothing new. Google, Bing, Safari and Yahoo have been personalizing search results for some time through tracking your browsing history. What is new is the sophistication of artificial intelligence and Big Data analytics.

With the burgeoning Internet of Things, the amount of customer and behavioral data is growing by the day. Even if Congress hadn’t cleared the way for internet services providers (ISPs) to sell your data, what marketers and advertisers know about customers was only going to increase thanks to the growing data fiefdoms of Google, Facebook, Apple, Amazon and Microsoft.

For good or ill, the ability to use that information to target the right customer with the right message at the right time is maturing. In fact, even back in 2012 ,Target had the capability to use data mining to predict the pregnancy of a teenager before her father could deduce the news himself. Big Data has come a long way since then.

In the case of local discovery, Big Data will help search engines personalize local results based on a user’s preference. The more the search engines know about you, the more relevant search results and maps will be.

For example, a search for nearby restaurants might include ranking factors such as your favorite dishes, food allergies, price point, time of day and how long it was since your last visit. Meanwhile, a search for a nearby product such as shoes might be filtered by your favorite brand, shoe color, size and any ongoing sales.

However, knowing your customer and targeting your customer are two different things. There needs to be a means of surfacing local information in a unified way, and that need will undoubtedly be addressed by digital assistants.

Digital assistants and voice search

Digital assistants will serve as the connection between customer profiles and the preferred locations and products around them.

Digital assistants will be everywhere. On your phone, in your car, your house, your office — everywhere and inside everything connected to the internet.

The ultimate goal of Google Assistant, Amazon Alexa, Microsoft’s Cortana and Apple’s Siri is to become that universal connection between the physical and digital worlds.

In the context of local discovery, think of a digital assistant as your very own personal Rick Steves, providing you with everything you’d ever care to know about a location — and then some.

This omnipresent assistant, part tour guide, part planner, part shopping liaison, will provide users with the most relevant and personalized local recommendations for anything you can imagine.

And thanks to voice search, digital assistants are always listening.

Google Home and Amazon Alexa operate in this mode by default, and Apple’s latest iPhone update is pushing users to set up voice activation for Siri.

In addition to enabling ambient listening, voice activation establishes voice biometrics, which will allow digital assistants to become device-agnostic.

Whether it’s smart cars, smart homes or smart offices, the ability to distinguish between users is critical to translating your personal preferences regardless of location or device. This will provide a consistent user experience without a disruption to conversational context.

In fact, Google Home recently made progress on this front by being able to recognize up to six different voices from one device. It’s not hard to extrapolate this trend to the point that digital assistants will be able to recognize who you are regardless of where or what device you’re using.

Soon you’ll be able to make dinner reservations by talking to the digital assistant embedded in your hotel room, order an Uber from the digital assistant on your phone as you walk to the lobby and check your flight from the digital assistant inside your autonomous Uber — all without breaking the conversational context with your digital assistant.

Augmented reality

With the rise of voice search, it’s also necessary to replace the traditional screen on your phone and monitor. A picture is worth a thousand words, so it’s unlikely that even a sweet-talking digital assistant will replace our need to visualize what’s in front of us.

As I outlined in a previous article, the solution to traditional screens is to replace them with augmented reality — your smartphone transforming into smart glasses. Based on Facebook’s recent plans for augmented reality, this indeed seems to be the direction we’re heading.

In my mind, augmented reality is likely to be one of the more exciting and less privacy-invasive developments of local discovery. You’ll be able to scout out a local restaurant, visualize the precise location of a product on a shelf or interact with custom location-based content triggered with beacons. Which brings me to the final trend you should be keeping an eye on.

Beacons

Proximity targeting will flourish with the rise of augmented reality and digital assistants.

Beacons are perfect for surfacing content in a user’s immediate proximity. The challenge right now is alerting users to beacons. However, if everyone has a digital assistant embedded in their augmented reality glasses, it will be easy for users to discover beacon content and have that content personalized based on personal preferences.

Whether it’s triggering a coupon for a customer’s most likely purchase as he walks by a store entrance or promoting a fast food restaurant as a vehicle exits the interstate off-ramp, the potential for beacons is tremendous.

Start preparing now

Many of these developments might seem too far out in the future. However, technology is evolving at an exponential rate. The time to start preparing and laying the groundwork for these marketing developments is now.

Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.

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Author: Brian Smith

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Search Buzz Video Recap: Google Owl & Updates, AMP Bugs & How Search Works

This week in search, Google documented their fake news efforts code named Project Owl. We covered a potential Google algorithm update, but it is unclear if there really was a big update. Google told publishers to noindex content from the AP, Reuters and other feed sources. Google released their new how search works site and with that shared some numbers of their search tests and launches. Google said they have no plans to boost the HTTPS ranking signal. Google said links from high traffic pages aren’t any more valuable. Google’s request indexing doesn’t replace sitemap files. GoogleBot doesn’t understand audio in podcasts. Google said they can check out SEO agencies that are scamming. Google seems to have AMP bugs in the search results, they also had an analytics issue with AMP. Google said patents and research papers are good but they don’t mean they use it in their ranking algorithms. Google updated the how search works site. Google added more review filters to the local pack. Google is testing carousels in the hotel booking feature and they are also testing call to actions there. That was this past week in search at the Search Engine Roundtable.

Make sure to subscribe to our video feed or subscribe directly on iTunes to be notified of these updates and download the video in the background. Here is the YouTube version of the feed:

For the original iTunes version, click here.

Search Topics of Discussion:

Please do subscribe via iTunes or on your favorite RSS reader. Don’t forget to comment below with the right answer and good luck!

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Author: barry@rustybrick.com (Barry Schwartz)

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Amazon beats expectations in Q1 2017 with 23% jump in revenue

Amazon crushed expectations with its Q1 2017 earnings report Thursday.

The company reported net sales revenue of $35.7 billion, a 23 percent spike from Q1 2016’s revenue of $29.1 billion. That’s just slightly above what analysts expected. The bigger surprise was earnings per share (EPS) of $1.48, way above the $1.13 that analysts had predicted. Amazon’s EPS a year ago were $1.07.

In Amazon’s earnings announcement, CEO Jeff Bezos specifically called out the success of his company’s recent investments in the Indian e-commerce market:

“Our India team is moving fast and delivering for customers and sellers. The team has increased Prime selection by 75% since launching the program nine months ago, increased fulfillment capacity for sellers by 26% already this year, announced 18 Indian Original TV series, and just last week introduced a Fire TV Stick optimized for Indian customers with integrated voice search in English and Hindi,” said Jeff Bezos, Amazon founder and CEO. “We’re grateful that customers are responding — Amazon.in is the most visited and the fastest growing marketplace in India. It’s still Day 1 for e-commerce in India, and I assure you that we’ll keep investing in technology and infrastructure while working hard to invent on behalf of our customers and small and medium businesses in India.”

The company’s stock, which closed Thursday at $918 per share, was trading up an additional 3 to 4 percent after hours and hovering around $950 per share.


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Author: Matt McGee

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