Google’s Chrome will change cross-site cookie handling, ‘aggressively’ tackle fingerprinting

Though the cookie is exceeding its shelf-life, the change stands to further shake up marketers’ remarketing, analytics and attribution efforts.

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As expected, Google announced coming changes to the way its Chrome browser handles cookies and addresses fingerprinting on Tuesday at its annual I/O developer conference. New tools in Chrome will allow users to block or clear third-party cookies more easily, Google said. The company also announced a browser extension that will show more information about parties involved in ad transactions and tracking.

Chrome’s new cookie handling. Google said “blunt approaches” to cookie blocking haven’t been effective for users because they treat all cookies alike — from first-party cookies used to keep users signed-in to sites to third-party cookies used for tracking — so it’s changing how cookies work in Chrome.

From a security standpoint, Google said this change will also help protect cookies from cross-site injection and data disclosure attacks by default. Eventually, Google said, Chrome will limit cross-site cookies to HTTPS connections.

In the coming months, developers will be required to specify explicitly which cookies are able to work across sites and potentially used to track users through a new mechanism based on the web’s SameSite cookie attribute. The SameSite attribute can be used to restrict cookies to first-party or same-site context.

In the weeds. Chrome 76 will include a new same-site-by-default-cookies flag, according to web.dev. Cookies without the SameSite attribute will not be available in a third-party context. Developers will need to declare cookies that need to be available on third-party sites to Chrome with SameSite=None. Google says this will allow Chrome users to clear cross-site cookies and leave single domain cookies used that are used for logins and site settings in tact.

Developers can start testing their sites to see how the cookie-handling changes will affect their sites in the latest developer version of Chrome.

Cracking down on fingerprinting. The company also said it is taking further measures to restrict browser fingerprinting methods that are used as workarounds to keep tracking in place when users opt out of third-party cookies.

Google said Chrome plans to “aggressively restrict” browser fingerprinting and reduce the ways browsers can be passively fingerprinted. “Because fingerprinting is neither transparent nor under the user’s control, it results in tracking that doesn’t respect user choice,” said Google.

The company added that it doesn’t use fingerprinting for personalizing ads or allow fingerprinting data to be imported into its ad products.

User cookie controls. Google said it will provide users will more information about how sites are using cookies and give them simpler controls for managing cross-site cookies. The company didn’t say what these changes will look like in the Chrome interface, but said it will preview the features for users later this year.

Ad data browser extension. The company also announced it is developing an open-source browser extension that will show the names of ad tech players involved in an ad transaction as well as the companies with ad trackers attached to an ad. The extension will also show the factors used for personalization. That will be the same information Google shows when you click “Why this ad”.

Why we should care. The end of digital advertising ecosystem’s reliance on cookies for tracking and attribution has been a long time coming. Cookies aren’t supported on mobile apps, and the mobile web and apps now account for the majority of ad spend. Google and Facebook have led a shift away from cookies to relying on deterministic IDs of signed-in users.

Chrome is not a first mover in this realm, either. It’s following in Apple’s Intelligent Tracking Prevention (ITP) footsteps. The latest version, ITP 2.2, will limit cross-site cookie tracking of users in Safari to one day. Earlier this week, Microsoft announced its Chromium-based Edge browser will also have new tracking controls for third-party cookies.

For marketers, the full impact of these changes and how users respond to the tools likely won’t be seen for months, but stand to have a significant impact on remarketing, analytics and attribution efforts. It’s also unclear if (or how much) Chrome’s new requirements will benefit Google with its first-party relationships with billions of users over other ad tech firms, as the Wall Street Journal has predicted.

The Chrome announcements come amid a broader PR campaign by Google aimed at would-be U.S. regulators. Google CEO Sundar Pichai published an op-ed in The New York Times Tuesday night titled “Privacy should not be a luxury good” in which he reiterated Google’s position that “a small subset of data helps serve ads that are relevant and that provide the revenue that keeps Google products free and accessible” and listed ways in which the company addresses user data. Pichai called for federal data privacy legislation in the vein of the EU’s GDPR. Google reportedly began lobbying for a “friendly” version of a federal law last summer.

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Why you want ‘clumpy’ binge-buying customers

By understanding binge purchasing, you can uncover a new metric to measure and predict CLV – and choose which customers to focus on and when.

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We’ve all heard of the term the “hot hand” in the context of sports. Basketball players go from missing every shot, to scoring in streaks. Sometimes players are in such a “zone” that he or she seemingly can’t miss a shot. Baseball players also tend to hit home runs in bunches.

Throughout my career and through my research at Wharton, I’ve studied the phenomenon of the “hot hand” as it relates to the way consumers tend to buy products and services or consume content. Simply put, customers who consume or buy content in bunches, then go away and come back and buy in bunches, are more valuable to companies than customers who buy at a steady pace.

Don’t believe me? Let’s take a deeper look at how measuring binge consumption by customers, or what I call “clumpiness,” can be applied to maximize Customer Lifetime Value, yielding stronger sales and marketing ROI over time.

Maximizing Customer Lifetime Value with clumpiness

CLV is universally accepted as a central tenet of marketing today. In both academia and practice, it is looked upon as a goal of firm value maximization. That is, more profitable firms recognize that CLV maximization yields greater cash flows and higher long-run profits.

Relatedly, mathematical models that allow these firms to predict CLV are commonly based on a framework commonly called RFM.

  •       Recency – How recently did a given customer make a purchase?
  •       Frequency – How often they made a purchase?
  •       Monetary Value – How much did they spend?

These are the cornerstones of CLV calculations and segmentation used by countless marketers and I’m here to tell you: They’re wrong!

Well, sort of. They are incomplete.

Through research, I have demonstrated and introduced that not only are RFM crucial components to calculating CLV; there is one additional dimension that MUST be factored in: clumpiness (C) or as some refer to it, binge consumption.

The hot hand

Let’s go back to the hot hand example and the player who is scoring points in bunches. Now, juxtapose over the world of marketing and consumers and you have clumpiness, AKA consumers who buy in bunches.

My research shows those who consume or buy content in bunches, then go away and come back and buy in bunches, are more valuable than other customers.

Let me put that another way. If a given brand knew both – how clumpy a consumer’s behavior is AND how frequently they buy – the better predictor when it comes to their future CLV is their clumpiness. I realize that may seem shocking, but it’s true. My research clearly illustrates that brands/marketers should be tracking someone’s clumpiness over time because that’s extraordinarily predictive of their CLV.

Across the board, marketers see far stronger results when they use RFMC data versus only using RFM. By focusing on clumpy consumers as their most valuable customers, brands can realize far stronger CLV and profitability.

With that overview in mind, let’s take a deeper look at what various brands have done to improve CLV and better target their marketing to encourage binge purchases by consumers.

Digital consumers behave more clumpily

We’re all familiar with binge-watching a series on Netflix, or other binge consumption of content from YouTube to gaming. But consumers have expanded this behavior beyond digital content and we’re now seeing it everywhere — from shared services such as AirBnB, Lyft and Uber to retail and online purchases.

A variety of different factors can drive clumpy behavior. In the case of content, the key driver is availability. For example, Netflix releases a new season of a given show, and suddenly everyone wants to watch it ASAP. They literally plan their lives around it.

Consumers can go weeks in between major purchases and then get the “hot hand” making multiple purchases or consuming an unusual amount of goods or services in a short period, or spending more money in a concentrated time.

The two sides of being clumpy and the demographic view

There are two types of clumpiness when it comes to consumers – visit clumpy and purchase clumpy. Consumers who are visit-clumpy are akin to the classic “window shoppers” of yesteryear. They visit both online and offline channels without necessarily making a purchase. In contrast, purchase-clumpy shoppers are far more valuable over time.

As a part of our research, we examined multiple retailers in specific product categories. Among the key findings were that millennials are more clumpy than other generations and that women are clumpier than men.

With marketers struggling to figure out how to market to millennials, this information can be helpful. By understanding clumpiness as a key facet of CLV, brands are turning the corner and seeing better results.

By understanding clumpy behavior, knowing to look for it and analyzing the level of clumpiness, marketers and other key decision makers gain a new metric for measuring and predicting CLV and choosing which customers to focus on and when. They can also gain a better understanding of customer satisfaction and react to it faster.

Defying the odds

When I first set out to conduct the research, I would have bet that the, findings would indicate that regular buyers were more loyal than those who buy in clumps. Well it turns out that my research, as well as others, suggests that regular buyers are in fact not more loyal.

Many times these are subscription customers and in fact, just buy without even thinking about their repurchase decision. A lot of research shows right now this is how you lose money. You take someone that buys in a regular pattern and try to upsell them because they don’t even think that they’re buying in a regular pattern.

We call it “poking the sleeping bear.” You poke somebody who’s just using your service regularly but isn’t even consciously … let’s say monthly making the decision to do so. And by your saying “Hey, why don’t you also buy …product?” “Holy cow! You mean I’m spending $300 a month on your product? Forget it! I cancel!” But your goal was to upsell them and instead you made them churn. So I’m not a strong believer in just observed loyalty. What appears to be observed loyalty over time, that’s not actually loyalty.

Final thoughts

I’m sure many of you reading this will have doubts. Many of you will want to stick to the tried-and-true RFM method and you are of course more than welcome to continue to do so. But I can tell you, without reservation, that if you do not begin to also factor in C (clumpiness), you will never get a true read on your customers.

Although recency/frequency/monetary value (RFM) segmentation framework, and its related probability models, remain a CLV mainstay, companies need to extend the framework to include clumpiness to predict future customer behavior successfully.

After studying thousands of data sets from companies across categories, we’ve found that C adds to the predictive power, above and beyond RFM and firm marketing action, of both the churn, incidence, and monetary value parts of CLV. Hence, we recommend a significant implementation change: from RFM to RFMC.

Measuring clumpiness has huge practical value. Clumpy consumers are worth more money and firms need to find them, and use marketing to drive customers to binge consume.

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Quick Hits CRO Tips Episode 4: What to Look For in Visitor Recordings

Welcome to Quick Hits CRO Tips from Crazy Egg! In this video resource series, we share advice, best practices, and strategies for how to boost your conversions, increase your revenue, and turn your visitors into customers — all in 2 minutes or le…

Quick Hits CRO Tips Episode 4

Welcome to Quick Hits CRO Tips from Crazy Egg! In this video resource series, we share advice, best practices, and strategies for how to boost your conversions, increase your revenue, and turn your visitors into customers — all in 2 minutes or less. This week we’re covering how you can use Visitor Recordings (also known […]

The post Quick Hits CRO Tips Episode 4: What to Look For in Visitor Recordings appeared first on The Daily Egg.

Quick Hits CRO Tips Episode 3: How to Use Snapshot Reports with Visitor Recordings

Welcome to Quick Hits CRO Tips from Crazy Egg! In this video resource series, we share advice, best practices, and strategies for how to boost your conversions, increase your revenue, and turn your visitors into customers, all in 2 minutes or less. Thi…

Quick Hits CRO Tips Episode 3

Welcome to Quick Hits CRO Tips from Crazy Egg! In this video resource series, we share advice, best practices, and strategies for how to boost your conversions, increase your revenue, and turn your visitors into customers, all in 2 minutes or less. This week we’re focusing on visitor recordings — an often overlooked, but extremely […]

The post Quick Hits CRO Tips Episode 3: How to Use Snapshot Reports with Visitor Recordings appeared first on The Daily Egg.

Here’s how to get the most out of your marketing analytics investment

Build organizational structure and develop analytics leaders who bridge data science with marketing strategy to improve your return on investment.

The post Here’s how to get the most out of your marketing analytics investment appeared first on Marketing Land.

Gartner recently published their Predicts 2019 research report, outlining several converging trends that pose a threat to CMOs and marketing organizations. The report also makes several bold predictions including that “by 2023, 60 percent of CMOs will slash the size of their marketing analytics departments by 50 percent because of a failure to realize promised improvements.”

The number one success factor for CMOs today is the ability to effectively leverage customer data and analytics. And yet, according to Gartner’s report, companies today are clearly not demonstrating consistent return on that investment, a problem which often stems from a lack of marketing analytics leaders and the organizational structure necessary to effectively translate data and insights into action.

To discuss in more detail, we chatted with one of the authors of the Gartner report, Charles Golvin, to explore what CMOs and marketing leaders can do to buck the prediction and drive stronger results for their marketing analytics investment.

Our conversation, coupled with my own experience, solidified five ways CMOs can improve return on their marketing analytics investment, while also reinforcing why it matters:

1. Build organizational structure to apply better data

Knowing how to effectively leverage customer data and analytics is the number one success factor for CMOs today. And yet, to fully leverage the power of analytics, companies need to develop organizational structure and processes to be able to identify, combine and manage multiple sources of data.

As Golvin puts it, “companies need to build a better pipeline of carrying data from its raw state to decision and action systems for data science leaders to apply insights and powerful analysis to determine the right action and right strategy.”

To build these pathways, companies need a strong methodology coupled with an approach for how data gets aggregated, digested and applied to their various marketing systems.

2. Develop analytics leaders who bridge both data science with marketing strategy

Another key success factor for companies is developing and hiring the right leaders who can bridge both data science and business strategy. Simply put, analytics leaders need to know enough about business to ask the right questions of data. Only then, can they apply data and models to yield better decisions and drive sustainable growth.

This is our philosophy at Wharton – preparing well rounded, analytically-adept business leaders who don’t ask what data can do for them, but what data is needed to increase customer lifetime value (CLV) and how to apply data and customer insights to shape brand strategy.

Gartner regularly conducts surveys about different challenges that CMOs and marketers face, and every year, the one that rises to the top is finding skilled data and analytics leaders to hire,” shares Golvin. “Companies also struggle to find those ‘unicorns,’ or people able to command both data science and business strategy.”

Golvin also pointed out that once a company does hire an analytics leader, companies need the right foundation in place to foster their success. “There’s no value to hiring a data scientist whose output leadership doesn’t understand or know how to implement.”

Too often, we see traditional marketing organizations that aren’t able to effectively apply analytics or don’t understand how to frame the questions for data scientists on their team. The reverse is also a common challenge: analytics leaders don’t grasp how to use data to shape the broader business and brand strategy.

3. Hire a Chief Analytics Officer, or up-level the importance of analytics

So how do companies up-level the importance of analytics and develop the data-driven culture, capabilities and leaders needed to successfully transform their organization? One trend we are seeing is the emergence of the Chief Analytics Officer or Chief Data Scientist across more organizations.

As Golvin notes, “we’re already starting to see the emergence of Chief Marketing Technology Officers, who are focused on deployment of the right technology, architecture and capabilities. The next trend may be marketing analytics leaders at the c-level, who are purely about analytics and understanding the data.”

When companies empower analytics leaders to lead strategy, it can transform the culture, providing a clear vision for what customer data will be used and how to reach the desired business impact. When companies fail to make this investment, it leaves high-caliber professionals in a quandary.

“Too often data science leaders end up doing grunt work such as basic data processing and preparation, rather than using their analytics mindset and abilities to drive actionable marketing strategy, separate the signal from the noise and improve marketing outcomes,” notes Golvin.

4. Focus on better data, not big data

An ongoing challenge organizations face today is what we call “better data, not big data.” Too often we see companies that are collecting data for data’s sake, rather than taking a lean approach where they only collect data when it helps to optimize the experience for their target customers or better prediction of future behaviors.

“As data becomes more integral to marketers, a ‘more is better’ attitude develops, without necessary consideration given to the downside risks,” notes Golvin. “Companies need to do a better job of being transparent about what data they use and how, as well as considering the pros/cons, and risks of incorporating that data into a profile of their customers. More data does not necessarily lead to greater business intelligence – and in many cases can expose the brand to issues that impact customer trust.”

Data collection is in no one’s interest when it’s not meaningfully tied to strategy.

5. Separate the signal from the noise to predict and optimize business outcomes

Improving ROI for marketing analytics requires constant learning and experimentation to separate the signal from noise. There’s no better way to learn about your customer than to see what works and what doesn’t.

While big data and machine learning are great to business intelligence, a well-controlled experiment can deliver far more value. Finding the most impactful experiments to run starts with asking the right questions and maintaining a test and learn mindset where you’re constantly evolving to improve the experience for customers. The iterative adaptation based on these experiments builds momentum.

Many marketers know the “Holy Grail” phrase “deliver the right product to the right person at the right time.” In the past, this was more difficult because we didn’t know where consumers were. Now when marketers use better data, they know where the customer was and is more likely to be – providing the foundation for the ultimate in contextual 1:1 marketing.

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Who’s Hiring in January 2019?

Here are our picks: Website Optimization Specialist – In Atlanta, SunTrust is looking for a specialist to be responsible for “developing and executing business strategies, processes and policies to enhance the sales and service experiences intrinsic to SunTrust’s digital spaces.” A/B Testing & Personalization Analyst – Join Barnes & Noble’s Optimization team in New York […]

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Here are our picks:

Website Optimization Specialist – In Atlanta, SunTrust is looking for a specialist to be responsible for “developing and executing business strategies, processes and policies to enhance the sales and service experiences intrinsic to SunTrust’s digital spaces.”

A/B Testing & Personalization Analyst – Join Barnes & Noble’s Optimization team in New York to “improve bn.com’s content, design, and usability for customers and to create unique experiences based on customers’ preferences and behaviors.”

Director-Digital Product Analytics & Testing –  Join the Enterprise Digital and Analytics team at American Express in New York.  They are looking for a leader to “provide value to the online card shopping experiences within the Global Consumer and Commercial businesses through customer data and measurement, insights through analytics techniques and experimentation.”

Marketing Manager, International Conversion – Ancestry is looking for a candidate to join their Conversion Marketing team in San Francisco.  This person is “responsible for improving and optimizing the user experience at each step in the conversion funnel with the end goal of maximizing revenue from visitors in each of Ancestry’s key global markets.”

Marketing Manager, A/B Testing & Optimization – Join AuthO’s Growth Team in “driving improvement in key engagement metrics and customer experience throughout the customer lifecycle.”

Director of B2B Marketing, Demand Generation – Join Vimeo’s B2B marketing team in New York to “scale qualified lead acquisition, build and continuously optimize digital marketing, account-based marketing (ABM), email automation, social, and event-based marketing channels.”

Sr. Analyst, eCommerce Direct to Consumer Analytics – Newell Brands is looking for a senior analyst in Hoboken, New Jersey, to drive “sustainable growth online through the best-in-class use of data and analytics.”

Digital Marketing Leader – Website Optimization – Join GE Healthcare in Wauwatosa, Wisconsin to “develop a rigorous testing and experimentation framework, and conceive, scope and implement experimentation initiatives to improve the website user experience and drive conversion rate optimization.”

Manager, Marketing Planning, Test & Analysis – Express is looking for an individual to lead the testing and optimization program in Columbus, Ohio, “starting with A/B & multivariate testing taking us into experience optimization and eventually personalization.”

 

Looking for a job or to fill a position?  Give us a shout and we’ll help spread the word in our next careers blog post.

 

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Building the essential marketing technology stack to fuel your experimentation program

We hear shouts of “hyper-personalization” constantly—a one-to-one customer experience is the pinnacle for many organizations today. Of course, this relies…Read blog postabout:Building the essential marketing technology stack to fuel your experimentat…

We hear shouts of “hyper-personalization” constantly—a one-to-one customer experience is the pinnacle for many organizations today. Of course, this relies...Read blog postabout:Building the essential marketing technology stack to fuel your experimentation program

The post Building the essential marketing technology stack to fuel your experimentation program appeared first on WiderFunnel Conversion Optimization.

Free Guide: How to Strategize & Execute Profitable Personalization Campaigns

When I speak with our clients, it often strikes me how many of them feel overwhelmed by the very idea of personalization. Our imagination, often fueled by the marketing teams of various software companies, creates a perfect world where personalization enables every interaction to be completely custom for every individual. In this dreamland, artificial intelligence […]

The post Free Guide: How to Strategize & Execute Profitable Personalization Campaigns appeared first on Brooks Bell.

When I speak with our clients, it often strikes me how many of them feel overwhelmed by the very idea of personalization.

Our imagination, often fueled by the marketing teams of various software companies, creates a perfect world where personalization enables every interaction to be completely custom for every individual. In this dreamland, artificial intelligence and machine learning solve all our problems. All you have to do is buy a new piece of software, turn it on, and…BOOM: 1:1 personalization.

As a data scientist, I’ll let you in on a little secret: that software only provides the technological capability for personalization. Even further, the algorithms found within these tools simply assign a probability to each potential experience that maximizes the desired outcome, given the data they have access to. Suffice to say, they’re not as intelligent as you are led to believe.

If you caught our first post in this series, you already know that we define personalization a bit more broadly, as any differentiated experience that is delivered to a user based on known data about that user. This means personalization exists on a spectrum: it can be one-to-many, one-to-few, or one-to-one.

And while there are many tools that enable you to do personalization from a technical standpoint, they don’t solve for one of the main sources of anxiety around personalization: strategy

Most personalization campaigns fail because of a lack of a strategy that defines who, where and how to personalize. So I’ve put together a free downloadable guide to help you do just that. This seven-page guide is packed full of guidelines, templates and best practices to strategize and launch a successful personalization campaign, including:

  • Major considerations and things to keep in mind when developing your personalization strategy.
  • More than 30 data-driven questions about your customers to identify campaign opportunities.
  • A template for organizing and planning your personalization campaigns.
  • Guidelines for determining whether to deliver your campaigns via rule-based targeting or algorithmic targeting.

Free Download: Plan & Launch Profitable Personalization Campaigns.

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Thank You + Brooks Bell’s Best of 2018

It’s January 3, and if you’re like us, you’re already heads down at your desk and neck deep in emails. But we’d be remiss if we didn’t take a minute to reflect on the previous year. In November of 2018, we quietly celebrated 15 years of being in business. When Brooks Bell was founded, experimentation was in […]

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It’s January 3, and if you’re like us, you’re already heads down at your desk and neck deep in emails. But we’d be remiss if we didn’t take a minute to reflect on the previous year.

In November of 2018, we quietly celebrated 15 years of being in business. When Brooks Bell was founded, experimentation was in its infancy. But despite all the changes we’ve experienced since then, one thing remains true: it is the opportunity to connect with so many interesting people that are solving big problems for their business that makes our work worthwhile. Thanks for walking with us.

A look back at some of our big moments from 2018

Winning like Winona

In January, our Founder & CEO, Brooks Bell, was recognized as one of 25 women who rocked digital marketing in 2017. Later in the year, she was also announced as a Southeastern Finalist for EY’s Entrepreneur of the Year award. 

We also celebrated 2017’s record-breaking growth, were recognized as Optimizely’s North American Partner of the Year, and we garnered our local business journal’s Best Places to Work award.

Getting Lit with Illuminate

Fun fact: We originally built Illuminate to help us better manage and iterate upon our clients’ tests. Over time, we got so much great feedback, that we decided to make it available to everyone this year.

Now, with a successful beta launch under our belt and even more new features being added to the software, we’re excited to see where this new endeavor takes us in 2019.

F is for Friends, Fun and…Fear?

In October, things got a little spooky around the office and it had everything to do with Scott, our Director of Sales, who decided to channel his inner Ellen Degeneres for the day (much to our colleagues’ horror). Watch the video if you dare.

Making Bacon for our Clients

Back in 2014, we set a Big Hairy Audacious Goal to achieve $1 billion in projected revenue for our clients. By the end of 2017, we’d reached $500 million. And this past December, we hit $1 billion. (cue ::gong::)

But we’re not resting on our laurels. We’ve set some aggressive goals for 2019, with a focus on personalization, and we’re pumped to get to work.

Brooks Bell takes the Bay Area 

In September, we officially opened the doors to our San Fransisco office. This decision came after years of working with clients on the West Coast and our desire to work even more closely with them. And with the Bay Area’s rich history of innovation, we can’t think of a better place to help more companies push their boundaries through experimentation.

Still Clickin’ 

Last May, we hosted our annual Click Summit conference. We might be biased but this remains one of our favorite events as it’s filled with meaningful connections and seriously impactful takeaways. 2019 marks our 10th Click Summit, and we’ve got big plans. Request your invite today.

2018 on the blog

 


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Who’s Hiring in December?

Here are our picks: Sr. Director – Customer Experience Leader – Equifax is looking for a Senior Director in St. Louis, Missouri, to lead the Customer Experience Team in “intuitive design workflows and overall customer experience as they interact with Workforce Solution products.” Senior Software Engineer, Build Automation – Blizzard Entertainment is “seeking a talented […]

The post Who’s Hiring in December? appeared first on Brooks Bell.

Here are our picks:

Sr. Director – Customer Experience Leader – Equifax is looking for a Senior Director in St. Louis, Missouri, to lead the Customer Experience Team in “intuitive design workflows and overall customer experience as they interact with Workforce Solution products.”

Senior Software Engineer, Build Automation – Blizzard Entertainment is “seeking a talented and enthusiastic software engineer to join the Hearthstone team” in Irvine, California to improve testing, building and developing Hearthstone through software automation.

Conversion Optimization Specialist – Vivint Smart Home is looking for an “action-oriented thought leader to partner with the digital marketing channel manager to optimize ad creative, product lifts in on-page response rates and improve conversion rates for Vivint’s digital marketing portfolio.” in Provo, Utah.

Head Of Customer Marketing – Kabbage is “looking for an extremely analytical, results-oriented leader to join their data science team in Atlanta with a passion for growing customer relationships and increasing the value of customer marketing.”

Associate Director of Experimentation – Marketing Analytics – Join Walmart in San Bruno, California and “help the World’s largest omni-channel retailer develop, promote and lead execution of a rigorous testing and experimentation roadmap.”

Senior Product Manager, Data & Analytics – In New York, HBO is “looking for someone who has a proven track record of leading teams to identify unique market and consumer requirements, with experience in digital products portfolio management.”

Digital Product Manager – Cole Haan is looking for a manager in New York to “own the front-end digital site experience on ColeHaan.com and drive the overall user experience, optimization efforts and road map.”

UX Manager (E-Commerce) – iHerb is looking for a UI/UX Manager in Orange County, California to “enhance iHerb’s customer experience on their industry-leading, global e-commerce site through design and maintenance.”

Senior Manager, UX Planning & Insights – Join Leapfrog Online’s Strategy & Insights team in Evanston, Illinois and “help lead the strategy and cross-channel, digital user experience planning for Leapfrog clients.

Senior, UX Development – Fidelity Investments is looking for a web developer in Durham, North Carolina to join the User Experience Design team.  This role will be “supporting the Health Care Group’s digital employee and employer platforms, which customers and plan sponsors use to manage their health and welfare benefits.”

Looking for a job or to fill a position?  Give us a shout and we’ll help spread the word in our next careers blog post.

 

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