Don’t Make It Weird: 5 Tips for Balancing Privacy & Personalization

Imagine a simple scenario: Your coworkers are participating in a fun run for charity and want you to join. You’re up for it, but you know you need a decent pair of running shoes. The logical solution is to go online, search for information about running shoes and identify a few possible options. You could […]

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Imagine a simple scenario: Your coworkers are participating in a fun run for charity and want you to join. You’re up for it, but you know you need a decent pair of running shoes.

The logical solution is to go online, search for information about running shoes and identify a few possible options. You could order the shoes from an online retailer, but because proper fit is important for running shoes, you decide to visit a specialty retailer at the mall. A salesperson there is friendly and knowledgeable. The store has a pair of shoes you like, in your size. They’re a bit more expensive, but the fitting service added value and there’s no additional shipping cost, so you purchase the shoes on the spot. The next weekend, you run the race and the shoes feel great.

This illustrates a relatively traditional model of consumer decision-making. It begins with a spark that motivates a search for a product. It leads to a research phase, and a consideration set is developed. It then progresses to some type of product experience that narrows the consideration set. Ultimately, a purchase decision occurs and an evaluation of the final product is made.

But today’s online customers may notice a glaring omission from the process: It occurs a week after the run, when you visit a news website. There, in the right column of the page, is an ad for a pair of running shoes. The ad is tailored to your expressed preferences, but not personalized enough to know that a purchase has already occurred.

Seeing these ads, which follow us around the web, can be annoying, unnerving, and even potentially embarrassing. Because the targeting is so crude, it’s obvious that we’ve exchanged some degree of privacy for a marginal—in this case questionable—convenience. And, if this exchange has happened so frictionlessly with one online retailer, how often is it happening elsewhere?

If you can relate to this, you’re not alone. Research has found that consumers generally dislike targeted and personalized advertising. So if personalization makes customers uncomfortable, does this means brands should stop using tailored messages, offers and experiences?

The answer is, decisively, no.

Here’s why: the same body of literature that outlines a negative attitude towards personalization, also highlights the undeniable benefits of personalization. When an ad or message—such as an email subject line—is tailored, even superficially, there is almost always an increase in engagement with the subsequent content.

This contradiction is known as the “privacy paradox.” Consumers are willing to make a long-term trade of personal privacy in exchange for a short-term benefit or convenience, like more relevant advertising or a more specific shopping experience.

But while attitudes toward privacy may contradict behavior, they certainly shouldn’t be ignored. When an ad, message, or experience feels intrusive or creepy, it can diminish the effect personalization could have on your customer and their overall perception of your brand.

Luckily, there are many ways to deliver personalized experiences while also making your customers feel more at ease about their privacy. Here are our tips.

1. Be transparent

Numerous studies have found that the more transparently personalized content is presented, the more effective—and importantly, the more broadly effective—it is.

While making explicit references to data collection and sharing policies can increase privacy concerns, it can also diminish the effect the concern has on consumer behavior.

In an extreme example, Facebook somewhat-recently rolling out a new way for users to see their ad preferences, after the company’s advertisement platform and practices faced scrutiny following the 2016 Presidential Election.

But it doesn’t have to be that complicated. For instance, simply including ad security icons, for example, has been shown to increase the effectiveness of tailored ads even when the icon is unrecognized.

In addition, referencing privacy policies can diminish concerns over data sharing and personalization, even if consumers never read the policy. One study found that consumers interpret a privacy policy as a blank slate populated with all the usual safeguards. This means, of course, the burden is on your company to draft and enforce a responsible privacy policy whenever consumer data is being collected.

2. Be public about your data security efforts

Unsurprisingly, reassuring your customers of data security and describing the efforts you’re taking to protect their data can make them feel more at ease. But the effectiveness of this approach really depends on how much your customers trust your brand and your site. Building this relationship is difficult and can be easily destroyed.

But, if your brand has built a relationship of trust over time and is authentically dedicated to preserving this relationship, referencing the care you have taken to secure private information can not only be a boon to overall perceptions but increase the effectiveness of personalization.

3. Be personal to the right people, at the right time.

In marketing, timing is everything; and the same goes for personalization, it turns out. In e-commerce, personalization is most effective when your customer has established a consideration set and a final decision is about to be made. Additionally, as your customer engages more with a product category or brand, they begin to expect and look forward to a more targeted, relevant experience.  

4. Let newer customers opt-in to personalization

When it comes to moving customers toward a purchase, personalization is more effective in the “pull” direction than in the “push” direction. This means that you should implement personalization with more loyal customers and especially those who have requested more tailored experiences.

For new customers, we suggest waiting to provide personalization until a visitor has shown a specific interest in your company or product: they’ve viewed a few pages on a website, downloaded your app or signed up for your email newsletter. Once this happens, offer a dialog asking “Would you like a more personal shopping experience?”

While it’s true that many visitors may choose to continue on their own, others may not. This also gives you an early opportunity to show your brands’ interest in providing a relevant, convenient shopping experience, which may come into play later once they become loyal customers.

5. Let your customers run the show

Perhaps the most unsettling recommendation for balancing privacy and personalization is to give up some control over the degree of personalization consumers experience. Doing so evokes many of the tips we’ve already covered: it improves transparency, allows consumers to opt into personalization, and helps to build trust. Additionally, offering this service has been found to dramatically improve the effectiveness of personalization, even when some customers actually change settings beyond the default.

Personalization is a powerful tool. The effect personalized messages and experiences have on customers, however, is variable and possibly unpredictable. It’s important that companies balance concerns for privacy and general feelings of intrusion when delivering personalized experiences. Testing these approaches we’ve outlined above will help make your personalization efforts feel less creepy and ultimately, increase the effectiveness of the customer experience.


Transform your customer experience through personalization.

Brooks Bells’ Personalization Jumpstart Program uses a comprehensive, five-step process to help top brands incorporate personalization across their customer experience. Learn more today >> 

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You’ve got a winner – now what?

Winner winner chicken dinner! Discovering a winning variation is one of the most exciting moments for an optimization program. It’s the moment when all the work that went into creating a test finally pays off. But while you should always take time to celebrate your team’s accomplishment, hold off on busting out the champagne just […]

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Winner winner chicken dinner! Discovering a winning variation is one of the most exciting moments for an optimization program. It’s the moment when all the work that went into creating a test finally pays off. But while you should always take time to celebrate your team’s accomplishment, hold off on busting out the champagne just yet. Your work has really only just begun.

Winning A/B tests can tell you a lot about your customers—what’s important to them, and why they respond the way they do. These results also enable you to quantitatively predict the impact it will have on your business’s bottom line (typically revenue), and project what that impact looks like over the next year.

Once you attribute a value to a winning experience, it’s critical that you also get the experience live on your site. This ensures you’re not leaving money on the table and also maximizes the impact of your testing program.

But to do this, you and your engineering team have to be on the same page. That is, you have to not only understand the way they work, but you also have to deliberately establish a process for implementing winners into your code base.

Most engineering teams operate using the Agile Method.
If you’re unfamiliar with Agile…well, first, what rock have you been living under? (Just kidding. But really?) Agile is a project management method that relies on incremental, iterative work sequences called sprints. For website developers and engineers, shorter sprints usually last 1-2 weeks and longer sprints last 3-4 weeks.

Most Agile engineering teams organize their projects by way of a prioritized backlog. This backlog is often managed by the product team, though other teams can request additions as needed. During each sprint, developers will work to add features and make other site updates based on what’s listed in the backlog.

During a sprint planning meeting, it’s important that you communicate the importance and impact of your winning experience. The higher the impact, the higher the priority, and the more likely it’ll be included in the upcoming sprint.

Of course, delays are common; particularly when your shared development resources are balancing many different priorities.

As an interim fix, you can use your testing tool to push the winner to production.
To do this safely, end the test campaign and duplicate the code into a new campaign, allocating 100% of traffic to the winner. We advise this method because pushing the winner through the original test campaign would risk displaying the losing experience to returning visitors who previously qualified for that experience.

Of course, there are risks to using a testing tool in this way—even if it’s only a short-term solution. While you might be able to cash-in quickly on your winning test, you could also face interference with future tests, maintenance issues and reduced page performance.

Beyond analyzing your results and getting your winner into production, there’s one final step following the identification of a winning test: capitalize on the win within your organization.

Communicating big wins for the business and customer insights drive momentum and support for experimentation within your company. Create powerful case studies; hone your storytelling technique to ensure you leave a memorable impression. Share your successes on Slack, by email, at town halls, or host a webinar…the opportunities are endless. Find the communication channel that catches the most attention in your organization, and run with it!

In our experience, cross-functional alignment is the biggest barrier and the largest contributor to the success of an optimization program. Have any additional ideas or examples of ways to create alignment around testing between engineering, product and optimization teams? Let us know in the comments!

Does your optimization process feel like less like a process and more like organized chaos? We’d love to help. Learn more about our services or contact us today.

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Unlocking the True Power of Testing & Other Takeaways from Brooks Bell’s Interview With Ambition Data

Recently, our Founder and CEO, Brooks Bell, sat down with Allison Hartsoe, host of the Customer Equity Accelerator—a podcast produced by Ambition Data. Listen to the full podcast or read on for a few highlights from their conversation:  On what inspired her to build an experimentation consultancy… Originally, Brooks founded Brooks Bell Inc. in 2003 as […]

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Recently, our Founder and CEO, Brooks Bell, sat down with Allison Hartsoe, host of the Customer Equity Accelerator—a podcast produced by Ambition Data. Listen to the full podcast or read on for a few highlights from their conversation:

On what inspired her to build an experimentation consultancy…

Originally, Brooks founded Brooks Bell Inc. in 2003 as a website development agency. After working with a few local clients, a chance introduction led to her first major experimentation client, AOL.

Today, you might think of AOL as one of the [now-extinct] internet dinosaurs, but even back in the early 2000s, the media giant was facing its fair share of challenges. According to one story by Time Magazine, despite having 34 million members in 2002, AOL was battling slowing subscriber growth, falling ad revenue and exorbitant operational costs. 

So, the company turned to experimentation. “AOL had the right environment to build a testing culture,” said Brooks. “They had a closed technology environment, their own analytics platform, and their data was clean and connected.”

Back then, AOL relied on pop-ups to drive new subscriptions. Working with Brooks, the company issued a challenge: design a new subscription pop-up that would beat the control experience. And so, drawing from her background in design and psychology, she did—and then she did it again, and again, and again.

But that was just the start. As other large companies began to rely more on the digital space to drive their business, Brooks saw an opportunity to help them tap into the power of experimentation.

“We realized that no one was testing!” said Brooks. “No other large companies had the data, culture and processes in place to test. So we set out to help them build the data fidelity and really recreate what we saw at AOL in those early years.”

On the difference between optimization and experimentation…

It’s one of the more common questions we get: “Brooks Bell is an experimentation consultancy. What’s that? What’s the difference between experimentation and optimization?” As Brooks explains it, it all comes down to science.

By definition, experimentation is the application of the scientific method to determine something. And while optimization is one potential outcome of an experiment, true experimentation requires running tests without a prescriptive outcome or application.

To put it simply – you’re testing to learn. And as long as your results are statistically significant, there is always something to be learned from experiments—even those with flat or negative results.

On how to unlock the real power of experimentation…

Today, in the age of Amazon, a customer-centric experience is critical. But for some established companies, this requires a bigger paradigm shift in culture and processes.  

“Customer-centricity requires rethinking metrics, the type of data you collect, how teams are organized, how teams are incentivized, how you communicate and also your core values,” said Brooks.

The true power of experimentation lies in its ability to align your customer needs with your company’s strategic goals and your program’s agenda. Furthermore, you can use experimentation to learn new things about your customers in a scientific way.

“Having statistically-sound customer insights can totally change how you organize your store, how you train your team, and how you structure your website,” said Brooks. “This is where testing programs can really drive change.”

To that end, we recently celebrated the launch of Illuminate, our customer insights software for testing teams and executives. Illuminate not only provides a place to store, share and learn from your experiments, but also a means to develop impactful customer insights.

“We launched Illuminate to provide a repository of great test examples, to learn from each other, and to build a library of great test case studies,” said Brooks.  This is because outside of the testing program, any key learnings from an experiment can get lost within the data. Illuminate solves this by encouraging deeper thinking about customers, their needs, preferences, and behaviors. 

Learn more about Brooks Bell’s experimentation consulting services. 

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How to Convince Your Boss to Invest in Experimentation: 5 Hard Truths

Would you rather have a root canal, or try to build something completely new at a huge, enterprise-level company that seems to be held together with nothing but red tape and internal politics? That may seem a bit dramatic, but obtaining buy-in for experimentation is a difficult challenge faced by many of our clients. Over […]

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Would you rather have a root canal, or try to build something completely new at a huge, enterprise-level company that seems to be held together with nothing but red tape and internal politics?

That may seem a bit dramatic, but obtaining buy-in for experimentation is a difficult challenge faced by many of our clients. Over the last 15 years, we’ve identified some hard truths about getting others to invest in testing. And in the spirit of “being real,” (one of our core values) we’ve decided to share them with you.

1. You have to bait the hook to suit the fish.

“The world is full of people who are grabbing and self-seeking. So the rare individual who unselfishly tries to serve others has an enormous advantage. He has little competition.” – Dale Carnegie, How to Win Friends & Influence People

We’ll take good ole Dale Carnegie’s advice on this one: if you want to convince someone to do something, you have to frame it in terms of what motivates them. In order to do that effectively, you have to be able to see things from their point of view.

“My go-to strategy for gaining executive buy-in for testing programs is to focus my discussions with them on the business impact of a well-run and successful testing program,” says Kenny Smithnanic, Director of E-Commerce at Ultra Mobile. “Most executives I’ve worked with want to see better company performance, even if they aren’t directly evaluated on this. So, I tend to discuss the exact revenue, orders, leads, and/or average order value increase that our business could realize from the accumulated gains of a successful testing program.”

When you’re pitching your experimentation program, position it as a program that works in service to other departments. Consider also your company’s big picture objectives and pinpoint where experimentation can work in direct support of those.

2. You’re gonna lose if you make it all about winning. 

Managing expectations is critical. Optimization is as much about learning about your customers as it is about landing some quick wins. And learning sometimes requires failure. Or, in this case, a few flat or losing tests. In fact, the industry win rate is actually 25%. If the expectation is that every test has double-digit lifts, it’s going to be a rough road ahead. 

All that said, here are a few strategies to manage expectations for your program.

Include executives in the ideation process. Let them see how your team is using data, generating lots of great testing ideas and working collaboratively. Including them in this process also provides them with a sense of ownership and investment to see how a strategy performs.

Develop a consistent (in frequency, timing and format) reporting structure. As you’re reporting the results of each experiment, begin by framing it in the context of your company’s larger goals. Don’t make the mistake of only focusing on the winning experience. Rather, walk your stakeholders through each variation individually and the resulting insights based on their performance.

State what’s next on your priority list, based on these results. This builds anticipation for your next round of tests, setting you up for future success, regardless of individual results.

3. Proving people wrong doesn’t convince them you’re right.

Avoiding pushback to your ideas requires three things:  Knowing what you’re up against, anticipating challenges and being open to others’ solutions.

Because executing tests often requires cross-functional support, you may have to take a test and learn approach to your experimentation program. You might also have to make a few compromises or adopt short-term solutions along the way.

Ultimately, if you’re seeking to make experimentation a core competency at your organization, you have to bring others along in the process. This means that as problems arise, it’s okay to recommend a solution, but you also have to be open to trying others’ solutions as well.

Only by solving problems together will you be able to build a high-functioning experimentation program and team.

4. You’re not going to blow anyone’s mind by using big words or snazzy acronyms.

In fact, when you’re trying to get people on board with testing, using super technical jargon can actually work against you.

Consider, for instance, the difference between “experimentation,” “testing,” and “optimization.” To you, these terms might mean the same thing, but to your boss, they may evoke different meanings.

So when you look to pitch your experimentation program, use terms that are familiar, accessible and aren’t at risk of being misinterpreted.

The same goes when introducing testing terminology to the broader organization. There are tons of acronyms associated with experimentation—RPV, AOV, UPT—the list goes on. Be sure you are decoding them until your team is more familiar. Revenue per Visit, Average Order Value, and Units per Transaction communicate far more meaning than an acronym.

Finally, consistency and intentionality are key here. Develop a common language for experimentation through trainings, lunch-and-learns and/or a company-wide roadshow. Finally, be sure that these terms are reflected in your internal processes: within meetings, in status reports, playbooks and in other means of communication.

5. Getting buy-in is not a one-time event.

You have to lay the groundwork. You have to build trust and credibility. You have to follow through. And through it all, you have to be a generally good person to work with.

Experimentation is amazing because it is supported through quantitative data and statistically significant results – making it a very quantifiable and persuasive case,” says Suzi Tripp, Senior Director of Experimentation Strategy at Brooks Bell.  “When you can share an experiment and tie it directly to incremental gains, it’s a powerful statement.”

But even if you get executive support for your program, you simply can’t expect everyone else to get on board immediately. In fact, having that expectation can lead to conflict and tension between teams, and cause a lot more internal problems.

To address this, we suggest working gradually: start out by working with one group, generate a success story, and share it through your internal communication channels, and keep going from there. Only by sharing your stories will other departments begin to be interested in harnessing that success as well.

Have ideas for other strategies to obtain buy-in for testing at your organization? We’d love to hear what’s worked for you. Share your story in the comments.

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How to hire your testing unicorn (without using magic)

When I was running my own testing program, I was in desperate need of an associate to help me manage my small (but mighty!) team. My single associate and I were launching tests left and right and we were unable to do anything other than focus on the day-to-day of the program. A job description […]

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When I was running my own testing program, I was in desperate need of an associate to help me manage my small (but mighty!) team. My single associate and I were launching tests left and right and we were unable to do anything other than focus on the day-to-day of the program.

A job description had been posted and the company’s recruiters were doing everything they could to find the right hire.

I remember reaching out to an old friend of mine to see if she knew anyone who might fit the role. I told her that I was looking (simply) for a data-driven individual with stellar communication skills and the ability to manage several complicated web projects at one time.

“Oh,” she said. “So you’re looking for a unicorn.”

“No, Susan… I’m looking for a Testing Specialist.”

Now, I don’t want to be too dramatic here, but this unicorn revelation did rock my world a bit. (It also made me want a bowl of rainbow sorbet with sprinkles… but I digress.)

When I finally overcame this existential testing crisis, I realized that I believed, deep down, that testing unicorns did exist. But I also knew that due to magic (obviously), I might never find one.

There were three main things I was looking for in my unicorn:

  1. Strong analytics skills and the ability to develop advanced data-driven recommendations
  2. Amazing communication skills – for helping stakeholders understand and action off of that data
  3. Organized and efficient project management skills for planning and managing the execution of test strategies

First, I had to assess which skills I already had on my team.

I took a look at my own skills and the skills of the team I had in place. To be honest, I’m much better at talking about analytics than I am at sitting behind a desk and doing a deep dive into the numbers.

My personal strength is in the communication realm of testing and my associate was an awesome project manager. So, it became pretty clear to me that there was a need for a strong analyst on our team.

Then, I had to decide what was teachable.

This is where things get controversial. Because teachable skills can really depend on the skills of the trainee, the trainee’s willingness to learn, and the skills of the trainer.

I did a quick poll here at Brooks Bell to see which skills my colleagues believe is the toughest to teach.

As you can see, many people here believe that good communication skills are hard to coach. And during my search for a Testing Specialist, I felt the same way.

I was pretty confident that I would be able to help my next hire become a better analyst or project manager, but I wasn’t so sure I could teach someone to communicate well in a stakeholder-facing role.

Finally, I had to decide if I could tweak my program structure

Depending on my next hire’s strengths, there were a few scenarios that I had to consider in order to structure my program without a unicorn. Here are a few examples:

If I decided to hire a strong analyst with weak communication skills

In this scenario, I would consider making this Testing Specialist role a non-stakeholder facing role. Because this person would not be project managing or communicating directly with stakeholders, they would be solely dedicated to analytics and free up the rest of the team’s time to focus on project management and stakeholder communication.

If I decided to hire a strong project manager with weak analytics skills

Because I believed that analytics skills were teachable, this associate could focus on project management in the beginning and slowly take on analytics work when they were ready.

If I decided to hire a strong communicator with weak project management skills

In this scenario, I would start by putting this associate in a stakeholder-facing role focused on analytics. After some time, I would begin training him or her on project management.

The magical lesson I learned

When I first approached this seemingly impossible task of hiring my next Testing Specialist, I was discouraged by the reality that I wanted so many specific skills in one individual.

But the truth is, Experimentation and Optimization is still a very niche industry, so finding a single person with so many abilities is going to continue to be tough for a while. That’s why I recommend first looking at the structure of your team, and then deciding which skills you feel comfortable teaching.

And always remember this: Testing unicorns do exist, sometimes we just have to help them find their wings.

Are you a testing unicorn looking for your next big challenge? Check out our monthly “who’s hiring” post for open positions in testing and personalization at top companies.


About the Author:

Sam Baker has eight years of experience running experimentation and digital analytics programs for major e-commerce brands. As a consultant at Brooks Bell, she helps global brands build and grow their testing programs.

In addition to her role at Brooks Bell, Sam is also an accomplished career coach, providing guidance to ambitious women looking to land their dream careers. Originally from Indiana, Sam now lives in Raleigh, North Carolina with her husband and her dog.

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