Category: Uncategorized

Article

Oct 4, 2022
7min read

The ROI of Experimentation

Emily Healy

Emily Healy

When you hear ‘A/B Testing’, do you think straight away of revenue gain? Uplift? A dollars and cents outcome? 

According to David Mannheim, CEO of the Conversion Rate Optimization (CRO) agency User Conversion, you probably do – and shouldn’t. Here’s why:

Unfortunately, it’s just not that simple. 

Experimentation is more than just a quick strategy to uplift your ROI. 

In this article we will discuss why we experiment, the challenges of assessing return on investment (ROI), prioritization, and what A/B testing experimentation is really about. 

Why do we experiment?

Technically speaking, experimentation is performed to support or reject a hypothesis. Experimentation provides you with valuable insights into cause-and-effect relationships by determining the outcome of a certain test when different factors are manipulated in a controlled setting. 

In other words, if there is no experiment, there is no way to refute a hypothesis and reduce the risk of losing business or negatively impacting metrics.

Experimentation is about prioritization, minimizing risk and learning from the outcome. The tests you choose to implement should be developed accordingly. It’s not necessarily about making the “right” or “wrong” decision, experimentation helps you make better decisions based on data.

In visual terms, experimentation will look something like this:

ROI frustration backlog

Online experiments in the business world must be carefully designed to learn, accomplish a specific purpose, and/or measure a key performance indicator that may not have an immediate financial effect. 

However, far too often it’s the key stakeholders (or HIPPOs) who decide what tests get implemented first. Their primary concern? The amount of time it will take to see a neat revenue uplift.

This tendency leads us to the following theory:

The ROI of experimentation is impossible to achieve because the industry is conditioned to think that A/B testing is only about gain.

Frustrations and challenges of ROI expectations 

You may be asking yourself at this point, What’s so bad about expecting revenue uplift from A/B tests? Isn’t it normal to expect a clear ROI?

It is normal, however, the issue isn’t just that simple.

We’ve been conditioned to expect a neat formula with a clean-cut solution: “We invested X, we need to get Y.”  

This is a misleading CRO myth that gets in the way. 

Stakeholders have come to erroneously believe that every test they run should function like this – which has set unrealistic ROI expectations for conversion optimization practitioners. 

As you can imagine, this way of thinking creates frustration for those implementing online experimentation tests.

Experiment backlog example

What people often overlook is the complexity of the context in which they are running their experimentation tests and assessing their ROI.

It’s not always possible to accurately measure everything online, which makes putting an exact number on it next to impossible. 

Although identifying the impact of experiments can be quite a challenge due to the complexity of the context, there are some online tools that exist to measure your ROI efforts as accurately as possible. 

AB Tasty is an example of an A/B testing tool that allows you to quickly set up tests with low-code implementation of front-end or UX changes on your web pages, gather insights via an ROI dashboard, and determine which route will increase your revenue.

Aside from the frustration that arises from the ingrained ROI expectation to be focused on immediate financial improvement, three of the biggest challenges of the ROI of experimentation are forecasting, working with averages, and multiple tests at once.

Challenge #1: Forecasting

The first challenge with assessing the ROI of experimentation is forecasting. A huge range of factors impacts an analyst’s ability to accurately project revenue uplift from any given test, such as:

  • Paid traffic strategy
  • Online and offline marketing
  • Newsletters
  • Offers
  • Bugs
  • Device traffic evolution
  • Season
  • What your competitors are doing
  • Societal factors (Brexit)

In terms of estimating revenue projection for the following year from a single experiment– it’s impossible to predict an exact figure. It’s only possible to forecast an ROI trend or an expected average. 

Expecting a perfectly accurate and precise prediction for each experiment you run just isn’t realistic – the context of each online experimentation test is too complex.

Challenge #2: Working with averages

The next challenge is that your CRO team is working with averages – in fact, the averages of averages.

Let’s say you’ve run an excellent website experiment on a specific audience segment – and you experienced a high uplift in conversion rate. 

If you then take a look at your global conversion rate for your entire site, there’s a very good chance that this uplift will be swallowed up in the average data. 

Your revenue wave will have shrunk to an undetectable ripple. And this is a big issue when trying to assess overall conversion rate or revenue uplift – there are just too many external factors to get an accurate picture.

With averages, the bottom line is that you’re shifting an average. Averages make it very difficult to get a clear understanding. 

On average, an average customer, exposed to an average A/B test will perform… averagely. 

Challenge #3: Multiple tests

The third challenge of ROI expectations happens when you want to run multiple online experiments at one time and try to aggregate the results. 

Again, it’s tempting to run simple math equations to get a clear-cut answer for your gain, but the reality is more complicated than this. 

Grouping together multiple experiments and the results of each experiment will provide you will blurred results. 

This makes ROI calculations for experimentation a nightmare for those simultaneously running tests. Keeping experiments and their respective results separate is the best practice when running multiple tests.

Should it always be “revenue first”?

Is “revenue first” the best mentality? When you step back and think about it, it doesn’t make sense for conversion optimizers to expect revenue gain, and only revenue gain, to be the primary indicator of success driving their entire experimentation program.

What would happen if all businesses always put revenue first?

That would mean no free returns for an e-commerce site (returns don’t increase gain!), no free sweets in the delivery packaging (think ASOS), the most inexpensive product photographs on the site, and so on.

If you were to put immediate revenue gain first – as stakeholders so often want to do in an experimentation context – the implications are even more unsavory. 

Let’s take a look at some examples: you would offer the skimpiest customer service to cut costs, push ‘buy now!’ offers unendingly, discount everything, and forget any kind of brand loyalty initiatives. Need we go on?

In short, focusing too heavily on immediate, clearly measurable revenue gain inevitably cannibalizes the customer experience. And this, in turn, will diminish your revenue in the long run.

What should A/B testing be about?

One big thing experimenters can do is work with binomial metrics. 

Avoid the fuzziness and much of the complexity by running tests that aim to give you a yes/no, black or white answer.

binomial metrics examples

Likewise, be extremely clear and deliberate with your hypothesis, and be savvy with your secondary metrics: Use experimentation to avoid loss, minimize risk, and so on.

But perhaps the best thing you can do is modify your expectations. 

Instead of saying, experimentation should unfailingly lead to a clear revenue gain, each and every time, you might want to start saying, experimentation will allow us to make better decisions.

Good experimentation model

These better decisions – combined with all of the other efforts the company is making – will move your business in a better direction, one that includes revenue gain.

The ROI of experimentation theory

With this in mind, we can slightly modify the original theory of the ROI of experimentation:

The ROI of experimentation is difficult to achieve and should be contextualized for different stakeholders and businesses. We should not move completely away from a dollar sign way of thinking, but we should deprioritize it. “Revenue first” is not the best mentality in all cases- especially in situations as complex as calculating the ROI of experiments.

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Article

Aug 18, 2022
4min read

Unleash your creativity: code once, customize infinitely

AB Tasty

AB Tasty

 

Say hello to Custom Widgets and goodbye to time-consuming back-and-forths when scaling ambitious customer experiences. With Custom Widgets, scale your best CX ideas across teams, brands and markets. AB Tasty has the largest widget library on the market, providing brands with over 25 pre-built ways to quickly engage consumers including scratch cards, NPS surveys and countdowns. But now we’re also giving you the ability to build, customize and share your own widgets! ?

Optimize the workflow between marketers, designers and developers

Custom Widgets are an innovation catalyst that fosters cross-team collaboration to bring ideas to life. Developers can now create highly customizable widgets following a step-by-step process. They simply code the different parts of the widgets using HTML, CSS and JavaScript and add various configuration options?‍?.  This allows designers to easily tailor the widgets and ensure they meet brand guidelines ?‍?.  Marketers can then customize them for their campaign needs ?‍♀️.The new possibilities to engage with visitors are endless: wheel of fortune, carousels, lightboxes, etc. These Custom Widgets result in an optimized workflow that saves everyone time but still delivers exciting experiences. ?

Create and scale a library of your best CX ideas

All Custom Widgets created (by developers, agencies, or AB Tasty) will be available in the widget library shared across all affiliates and accounts of a company. The library, accessible from the dashboard, is a great source of inspiration and ideation that will speed up time to market and facilitate deployment across brands and markets ✨. The widget library will also include our existing widgets with selected use cases from AB Tasty clients to further guide you in creating the best customer journey. And, like with any other widget, marketers can easily customize the content and combine it with AB Tasty’s targeting to create powerful personalized campaigns with no coding skills and in minutes ?‍♀️.

Not sure where to start?

In our new widget library, our users can already enjoy 2 custom widgets available on the platform, a Wheel of Fortune and a gradient CTA button, that they can duplicate and modify to dive into how they work. On that same page they can click on “Create a custom widget” and follow our step-by-step process ?. 

Why not try them now? If you’re looking for inspiration for your first Custom Widgets, check out our 30 Black Friday Tests ebook. It features successful tests from brands like Degrenne, a French cutlery and tableware retailer whose quality products are a staple in the hospitality industry. They wanted to accelerate the purchase process and provide a consistent omnichannel experience to their consumers. Using our widgets they gave their visitors the ability to see item availability in their local store ?.

If you want to replicate this, your developers can create a Custom Widget that leverages geolocation data to create a pop-up displaying product availability in nearby stores. Your customers will be able to reserve their items and opt for in-store pickup. Once available in the widget library, other brands or countries you work with can access it, modify it and leverage it to provide their visitors with an omnichannel experience.

To learn more check out the ebook ?:

With AB Tasty, let your good ideas take flight!

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Article

Jul 26, 2022
6min read

Using Failed A/B Test Results to Drive Innovation

Maddie Ostrander

Maddie Ostrander

“Failure” can feel like a dirty word in the world of experimentation. Your team spends time thinking through a hypothesis, crafting a test, and finally when it rolls out … it falls flat. While it can feel daunting to see negative results from your a/b tests, you have gained valuable insights that can help you make data-driven, strategic decisions for your next experiment. Your “failure” becomes a learning opportunity.

Embracing the risk of negative results is a necessary part of building a culture of experimentation. On the first episode of the 1,000 Experiments Club podcast, Ronny Kohavi (formerly of Airbnb, Microsoft, and Amazon) shared that experimentation is a time where you will “fail fast and pivot fast.” As he learned while leading experimentation teams for the largest tech companies, your idea might fail. But it is your next idea that could be the solution you were seeking.

“There’s a lot to learn from these experiments: Did it work very well for the segment you were going after, but it affected another one? Learning what happened and why will lead to developing future strategies and being successful,” shares Ronny.

In order to build a culture of experimentation, you need to embrace the failures that come with it. By viewing negative results as learning opportunities, you build trust within your team and encourage them to seek creative solutions rather than playing it safe. Here are just a few benefits to embracing “failures” in experimentation:

  1. Encourage curiosity: With AB Tasty, you can test your ideas quickly and easily. You can bypass lengthy implementations and complex coding. Every idea can be explored immediately and if it fails, you can get the next idea up and running without losing speed, saving you precious time and money.
  2. Eliminate your risks without a blind rollout: Testing out changes on a few pages or with a small audience size can help you gather insights in a more controlled environment before planning larger-scale rollouts.
  3. Strengthen hypotheses: It’s easy to fall prey to confirmation bias when you are afraid of failure. Testing out a hypothesis with a/b testing and receiving negative results confirms that your control is still your strongest performer, and you’ll have data to support the fact that you are moving in the right direction.
  4. Validate existing positive results: Experimentation helps determine what small changes can drive a big impact with your audience. Comparing negative a/b test results against positive results for similar experiments can help to determine if the positive metrics stand the test of time, or if an isolated event caused skewed results.

In a controlled, time-limited environment, your experiment can help you learn very quickly if the changes you have made are going to support your hypothesis. Whether your experiment produces positive or negative results, you will gain valuable insights about your audience. As long as you are leveraging those new insights to build new hypotheses, your negative results will never be a “failure.” Instead, the biggest risk would be allowing a status quo continuing to go unchecked.

“Your ability to iterate quickly is a differentiation,” shares Ronny. “If you’re able to run more experiments and a certain percentage are pass/fail, this ability to try ideas is key.”

Below are some examples of real-world a/b tests and the crucial learnings that came from each experiment:

Lesson learned: Removing “Add to Basket” CTAs decreased conversion

In this experiment, our beauty/cosmetics client tested removing the “Add to Basket” CTA from their product pages. The idea behind this was to test if users would be more interested in clicking through to the individual pages, leading to a higher conversion rate. The results? While there was a 0.4% increase in visitors clicking “Add to Basket,” conversions were down by 2%. The team took this as proof that the original version of the website was working properly, and they were able to reinvest their time and effort into other projects.

Beauty client add to basket use case

Lesson learned: Busy form fields led to decreased leads

A banking client wanted to test if adjusting their standard request form would drive passage to step 2 and ultimately increase the number of leads from form submissions. The test focused on the mandatory business identification number field, adding a pop-up explaining what the field meant in the hopes of reducing form abandonment. The results? They saw a 22% decrease in leads as well as a 16% decrease in the number of visitors continuing to step 2 of the form. The team’s takeaways from this experiment were that in trying to be helpful and explain this field, their visitors were overwhelmed with information. The original version was the winner of this experiment, and the team saved themselves a huge potential loss from hardcoding the new form field.

Banking client form use case

Lesson learned: Product availability couldn’t drive transactions

The team at this beauty company designed an experiment to test whether displaying a message about product availability on the basket page would lead to an increase in conversions by appealing to the customer’s sense of FOMO. Instead, the results proved inconclusive. The conversion rate increased by 1%, but access to checkout and the average order value decreased by 2% and 0.7% respectively. The team determined that without the desired increase in their key metrics, it was not worth investing the time and resources needed to implement the change on the website. Instead, they leveraged their experiment data to help drive their website optimization roadmap and identify other areas of improvement.

Beauty client availability use case

Despite negative results, the teams in all three experiments leveraged these valuable insights to quickly readjust their strategy and identify other places for improvement on their website. By reframing the negative results of failed a/b tests into learning opportunities, the customer experience became their driver for innovation instead of untested ideas from an echo chamber.

Jeff Copetas, VP of E-Commerce & Digital at Avid, stresses the importance of figuring out who you are listening to when building out an experimentation roadmap.  “[At Avid] we had to move from a mindset of ‘I think …’ to ‘let’s test and learn,’ by taking the albatross of opinions out of our decision-making process,” Jeff recalls. “You can make a pretty website, but if it doesn’t perform well and you’re not learning what drives conversion, then all you have is a pretty website that doesn’t perform.”

Through testing you are collecting data on how customers are experiencing your website,  which will always prove to be more valuable than never testing the status quo. Are you seeking inspiration for your next experiment? We’ve gathered insights from 50 trusted brands around the world to understand the tests they’ve tried, the lessons they’ve learned, and the successes they’ve had.

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Article

Jun 9, 2022
5min read

1,000 Experiments Club: A Conversation With André Morys of konversionsKRAFT

AB Tasty

AB Tasty

André Morys shares the key to a thriving business in today’s market: a fearless attitude toward innovation and experimentation

André Morys has been involved in the field of experimentation for almost three decades. The CEO and founder of konversionsKRAFT discovered the importance of the user experience upon launching his e-commerce optimization company in 1996. He followed the evolution of high-end UX measurement solutions and AB testing throughout the 2000s, turning his focus entirely to experimentation and experience optimization in 2010.

Powered by his fascination for measuring the outcomes of the customer and user experience, including the financial impact of optimizing them, André uses his expertise to guide his clients through the experimentation process in a clear and efficient manner.

AB Tasty’s VP Marketing Marylin Montoya spoke with André about cultivating an experimentation mindset – that is, how to build a culture of experimentation that embraces failure and risk-taking – in order to innovate in competitive markets as an experimentation-driven company.

Here are some of the key takeaways from their conversation.

Risk and failure are integral components of innovation

Many risk-averse companies hesitate to implement experimentation due to their mindset around failure. When adopting a culture of experimentation, it’s essential to understand the fact that, despite prior research and preparation, failure is a part of the innovation and testing process. Most tests will produce negative results … but this shouldn’t be interpreted as failure.

Overcoming our personal beliefs and shame around failure and encouraging managers to lead by example will allow companies to embrace the experimentation process. This means discussing and deducing insights from failures within a team setting and allowing it to be a learning opportunity. Experimentation offers the chance for teams to evolve in how they see, feel and talk about failure and to focus on being solution-oriented rather than striving for perfectionism.

André also explains that while experimentation may seem risky, it is actually a way to control the level of risk linked to innovation. With experimentation comes feedback, allowing you to gauge the success of a particular feature or improvement, as opposed to naively rolling it out without any prior experimentation and simply hoping for the best.

Experimentation should always be linked to strategic goals and measured

The ROI of experimentation comes in many forms. André uses a “digital experimentation framework” to implement the experimentation process and measure progress. In relation to his “Iceberg Model”, while the tip of the iceberg represents the metrics that are measurable, many important factors lay beneath the surface and are difficult to measure, resulting in people underestimating the value of experimentation.

“You cannot measure the influence of experimentation towards your company’s culture and how big and…sustaining this effect will be. It will be maybe 10 times more important than the actual uplift you create,” says André.

Once discovering the process, many managers agree that a shift in culture, inventiveness and velocity is more powerful than an improvement in metrics. Meaning, there is a shift toward changing what’s below the surface (company culture) in order to have a bigger long-term impact, rather than focusing on the tip of the iceberg (metrics).

A frequent mistake that companies make is not aligning their goals of experimentation to their strategic goals, creating the possibility that their experimentation might be irrelevant. Using the experimentation framework to optimize the process with shared goals from the beginning will produce the best outcome.

Use gamification to engage teams and build a culture of experimentation

Overcoming resistance within companies to jump into experimentation doesn’t have to be difficult; in fact, it can even be fun!

Involving teams with guessing games and placing bets on which test won, for example, is a simple yet effective method to educate people and to create a pull towards experimentation. This technique also creates a sense of humility and allows people to realize that their hypotheses may fail and the customer could have a differing opinion.

Documenting the experimentation process and results is also important for encouraging cultural change. Connecting people to the outcomes enables learning and better engagement with the experimentation process, which in turn increases motivation to further improve. Rather than pushing people towards experimentation, you can create a natural attraction to it and a sense of personal investment by using metrics as feedback and creating a flywheel.

An experimentation dashboard is key to showing the health of your experimentation process. André highlights the importance of running effective tests, being sure to focus testing on the right areas, rather than striving for high velocity and volume of experiments. The goal should be experimentation quality, not quantity, and ensuring that important metrics are stored on a dashboard to facilitate cultural change.

1000 Experiments Club André Morys

What else can you learn from our conversation with André Morys

  • The three catalysts for innovation and why experimentation is a key component
  • How perfectionism blocks experimentation and the evolving experimentation culture in Germany
  • The status quo bias and why management might resist change within an organization
  • How the pandemic shifted companies’ focus towards digital growth
About André Morys

André Morys has almost three decades of experience in digital growth and business optimization, founding konversionsKRAFT in 1996. Today, his company is the leading business optimization consultancy in the DACH region, with more than 80 consultants, designers and conversion experts.

Specialized in research, consulting and lecturing, André combines qualitative research, consumer psychology and behavioral economics with data and experimentation to deliver the most effective growth programs for enterprise clients.

André’s reading recommendations:
About 1,000 Experiments Club

The 1,000 Experiments Club is an AB Tasty-produced podcast hosted by Marylin Montoya, VP of Marketing at AB Tasty. Join Marylin and the Marketing team as they sit down with the most knowledgeable experts in the world of experimentation to uncover their insights on what it takes to build and run successful experimentation programs.

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Article

May 18, 2022
5min read

1,000 Experiments Club: A Conversation With Jeremy Epperson of ConversionAdvocates

AB Tasty

AB Tasty

Jeremy Epperson explains why startups should leverage conversion rate optimization to maximize growth.

Jeremy Epperson is about to change the way you approach growth in your business. The chief growth officer at ConversionAdvocates, a top-ranking CRO agency specialized in data analysis, takes a data-driven approach to identify the roadblocks in testing and optimize these processes for maximum effectiveness.

Over the past decade, he has launched CRO programs for 150+ growth-stage startups, creating a repeatable proven process for conversion rate optimization that can be implemented across different verticals and business sizes. By collating the insights gained from the different businesses, notably the common mistakes, Jeremy has gathered the expertise to facilitate CRO programs and avoid the steep learning curve that comes with launches.

In his conversation with AB Tasty’s VP Marketing Marylin Montoya, Jeremy delves into the granular level of data analysis and takes on topics that most people in CRO steer clear of.

Focus on customer experience optimization to catapult business growth

In today’s digital landscape, the old-school ideology of branding and push marketing is no longer an effective strategy. These days, customers have easy access to online reviews, forums and price comparison websites to inform their purchasing decision.

Rather than trying to control the customer journey, Jeremy recommends optimizing the experience of each of its four phases, using a data-driven, scientific-testing approach. This leads to the creation of different processes and reshapes the idea of optimization: The game-changing idea is that agility (allowing companies to move, learn and improve faster) can trump exorbitant budgets, thus allowing smaller companies to take market share from giants.

Passionate about being involved with teams on the ground level to “iteratively work through the entire process,” Jeremy touts CRO as the best mechanism and catalyst for growth, which challenges teams to rethink and rebuild processes and workflows, break down silos and build communication. Jeremy says this team-building aspect is more valuable from a CRO perspective than any individual winning test.

All data is equal: the value of wins, losses and flat tests in post-test analysis

When it comes to testing, certain results are deemed more “sexy” by marketers, and others are often swept under the carpet. However, Jeremy explains the utility of all test results, be that a win, a loss or a flat result, for informing how testing should evolve.

A string of inconclusive tests means that the testing has not been focused on what is actually blocking the conversion. “If we’re not targeted in on the things that are blocking them (users) from converting then we’re not going to see big movement in the conversion rates, so that’s really important,” says Jeremy.

When test results show big changes in the conversion rate, positive or negative, this indicates that an important part of the customer experience has been impacted. While winning tests are celebrated and losing tests shied away from, Jeremy advises that in both cases, the next step should be to double down on test variations to fully resolve the problem, creating at least three variations for each of those hypotheses.

Understand your customer and remove their purchasing roadblocks

Oftentimes, marketers, especially in smaller businesses, are reluctant to spend their budget on research and insights, opting for customer acquisition strategies involving ads and content. However, according to Jeremy, investing in research to better understand the customer can bring us closer to answering one question that’s key to creating the right growth strategy for your business: Why does your customer buy or not buy your product?

Research and testing can offer 360-degree insights into customer behavior such as their buying criteria, decision-making and their buying process in order to remove any conversion roadblocks. It could be as simple as creating an FAQ page to clarify primary questions, resulting in a 23% lift in lead conversion, as Jeremy exemplified.

Jeremy explains that businesses will naturally experience growth when they focus on offering a better customer experience, eliminating customer frustrations and roadblocks, which would otherwise cause them to abandon their purchase. This customer-centric mindset will actually have a direct positive impact on revenue and growth.

Jeremy Epperson

What else can you learn from our conversation with Jeremy Epperson

  • How to combine research and testing in CRO to double the average validated win rate
  • How to encourage teams to embrace the CRO process and cooperate across verticals
  • The inutility of customer personas and how to replace them
  • How to implement CRO for the first time
About Jeremy Epperson

Jeremy Epperson, chief growth officer at ConversionAdvocates, has worked in the field of startup growth and conversion rate optimization (CRO) for 14 years, as a consultant in his own businesses as well as part of digital agencies. Jeremy is passionate about researching, building and implementing processes to generate growth and has launched CRO processes within more than 155 growth-stage startups. He also specializes in customer journey mapping, CRO maturity assessments and marketing and customer research.

About 1,000 Experiments Club

The 1,000 Experiments Club is an AB Tasty-produced podcast hosted by Marylin Montoya, VP of Marketing at AB Tasty. Join Marylin and the Marketing team as they sit down with the most knowledgeable experts in the world of experimentation to uncover their insights on what it takes to build and run successful experimentation programs.

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Article

Apr 12, 2022
9min read

The Rise of the Experience Economy and How It’s Shaping the Future of E-Commerce

AB Tasty

AB Tasty

What is the experience economy?

Let’s say you have an online shop and in that online shop you have a product. Your product is designer eyewear and prescription glasses. A customer visits your online shop to learn about your product. That customer needs to determine which frames will suit their face and what size to order. A similar shop that sells similar products to yours offers free shipping and free returns of up to 3 pairs at no charge, or the use of a virtual reality assistant, via their mobile app, to help their customers make purchasing decisions without needing to visit a store. Your shop, though well-intentioned and bug-free, does not. The customer’s experience researching and selecting their product is what ultimately drives their decision-making process, and they purchase from the other shop. And the next time they need glasses, they purchase from that other shop again. That’s the experience economy.

What is the experience economy

In the experience economy, finding a differentiating edge is crucial for brands (Source)

Expressed in more academic terms, the experience economy is the packaging of goods and services into a bundle such that the experience of acquiring or consuming is the key selling point – it’s the reason the customer came into your shop in the first place.

In 1998, two Harvard researchers published an article detailing the concept of the experience economy for the first time, using a birthday cake analogy to eventually draw out the definition we see above. These days, the concept is more important than ever, as the rapidly evolving digital transformation of the way we consume information and goods creates a never-ending, multi-channel interaction between brands and consumers. And it’s key to your overall business success.

How e-commerce brands can succeed in the experience economy

In the age of digitalization, not only do all brands have websites, incorporating an e-commerce platform for online sales, but they also have Facebook, Instagram, TikTok and Snapchat accounts, more than likely a YouTube channel, a web browser adapted to mobile devices and an app to sit alongside it. In short, multiple channels and touchpoints for their customers to interact and engage with them, and multiple opportunities to create experiences to acquire new customers and drive sales. This all makes for a non-linear shopping experience, and requires careful examination of what customers expect on which channel and at which time.

How the experience economy is shaping the future

A customer-first mindset is crucial for businesses that are looking to win the digital CX game (Source)

How can brands adapt to shifting consumer preferences

At AB Tasty, we’re convinced that the brands opting for a “business as usual” approach will quickly be left in the dust. Customers expect better servicing, more meaningful interactions and suggest that they’ll spend more when brands deliver. This means having a strategy that considers multiple channels, across physical, digital and social touch points, and adapts to the preferences of each individual so that interactions remain authentic and personal. If you’re engaging with customers without being able to have in-person contact, experience matters even more, because consumers still want to be seen as individuals with their own unique needs. Ultimately, their experience will influence their buying decisions and according to Salesforce, 66% of consumers expect companies to understand their unique needs and preferences.

The shift in brand-consumer interactions

Create a personalized, relevant shopping experience for each customer (Source)

Figuring out what your customers want doesn’t just need to be a guessing game, experimentation is standard practice for the experience economy. In B2C environments, marketing teams test website performance using a range of experiments that examine layout, colors, purchase journeys, product information and visual features to ensure no stone is left unturned in maximizing transactions and revenue. And adopting an experimentation mindset really is a win-win. On the one hand, you’re identifying the best way to interact with your customers – identifying what they respond to and what they want – and on the other, you’re maximizing every opportunity to drive purchases and serve your bottom line.

Why prioritizing customer experiences matters

That’s all very well and good, you might say, but what difference does it really make? Plenty, in fact. Relevant and personalized consumer experiences are key to keeping your brand ahead of its competitors. Let’s explore some of the reasons for this.

  1. Loyalty is hard-earned and easily lost
    PWC’s 2021 Global Consumer Insights Survey found that 84% of shoppers trust brands that provide exceptional customer service, but one in three will walk away after just one negative shopping experience. In a similar vein, Qualtrics’ 2022 Global Consumer Trends survey reported that 60% of consumers would buy more if businesses treated them better, and also determined that 9.5% of your overall revenue is at risk from negative shopping experiences. These statistics still haven’t convinced you? Read on!
    ㅤ
  1. Seamlessness is synonymous with success
    You can design any number of gimmicks to attract attention, but it’s the seamless ones that stick. Take the Clarins Singles Day Wheel of Fortune promotion, where any customer landing on the brand’s desktop or mobile site in EMEA saw a pop-up to spin the wheel. They were then rewarded with one of six special offers, which was automatically added to their basket via a promo code at the checkout. This automatic add proved crucial: Results were strong across all key territories, with Ireland particularly notable, seeing a 495% increase in orders and a 585% increase in revenue. Clarins uncovered a clever, engaging offer and coupled it with a seamless UX process for their shoppers, delivering simply stunning results.Clarins case studyClarins delivered a customer experience on par with their clients’ expectations (Source)
    ㅤ
  2. Stagnate and you’ll be left behind
    To innovate or not to innovate, is it even a question? If you’re thinking about it, then your competitors almost certainly are too. And if you’re not trying something new, you almost certainly risk falling behind. While bug-free websites and a smooth journey through the purchase funnel is great, it’s also the bare minimum that you should be doing. Salesforce found that 91% of customers are more likely to make a repeat purchase from a company after a positive customer experience. Delivering a seamless, multichannel experience across all business interactions is integral to staying ahead and it’s clear there is still scope for brands to optimize.

4 examples of brands that are excelling in the experience economy

As we’ve seen in the above section, brands that embrace the experience economy are best-positioned to see increased loyalty, repeat business, and convert their customers into advocates for their products. Pushing beyond experiences into memorable interactions for their consumers has allowed some of the best-known brands in the world to gain further ground on their direct competitors, all while staying true to their core values. Let’s take a look at the best-in-class trends and examples of the experience economy model.

Nike

Nike is driven by delivering innovative products, services and experiences to inspire athletes. One such experience is their Nike Fit solution: an AI-driven app that allows you to virtually measure and fit your foot to ensure you choose the right pair of Nike shoes, no matter the style nor the shape of your foot, and without having to leave your living room.

Nike Fit

Nike introduces innovative solutions to their clients’ biggest point of friction (Source)

Sephora

In 2019, Sephora pioneered their intelligent digital mirror in the brand’s Madrid flagship, using the power of AI to deliver hyper-personalized experiences and product recommendations to shoppers. The mirror not only allows consumers to “test” products by displaying how they’ll render when applied, it also provides personalized product recommendations and suggestions based on an analysis of the customer’s features.

Sephora

Sephora develops new ways to offer their customers personalized recommendations (Source)

Starbucks

Starbucks has revolutionized their physical footprint by opening pickup-only stores in key, high-traffic locations where rental space is at a premium and busy lives mean in-and-out transactions are the order of the day. This store concept allows coffee lovers to order and pay ahead of time, via the Starbucks mobile app, and nominate the pickup location, for a speedy service that saves tedious, peak-hour queues. Not to mention a boost to sales per square foot, a key metric in the brick-and-mortar retail space.

Starbucks

Starbucks identifies their customers’ needs and delivers an optimal shopping experience (Source)

Asos

This online fashion retailer was founded in London in 2000, and now sells over 850 brands around the world. In identifying one of the key barriers to online shopping for clothes – choosing the correct size – Asos developed their Fit Assistant tool to ensure customers could navigate the online shopping experience hassle-free. Available on both desktop and mobile, Fit Assistant delivers personalized recommendations according to shoppers’ individual shapes and sizes.

Fit Assistant Technology - Recommend

Asos optimizes their customers’ online shopping experience (Source)

Why the experience economy is here to stay

Through a combination of rapid digital transformation, technological innovation of smart devices (phones, tablets, watches and more), and the increasing pace of our daily lives, the manner in which we consume products has evolved beyond mere acquisition. How we consume the product matters. How we feel about how we consume the product matters. How the brand ensures we enjoy our consumption of the product matters. And if your brand is not up for the challenge and staying ahead of the game, consumers will find one that is. It’s as simple as that. Evolve, innovate, and deliver seamless brand experiences, and you’ll lead the competition, win market share and generate growth.

If you’re looking for some guidance on how to deliver impactful brand experiences that will “wow” your customers, draw inspiration from the first-ever digital customer journey that maps out how to drive optimization and innovation to take your customer experience to the next level.

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Jan 26, 2022
3min read

Introducing AB Tasty’s New Navigation

AB Tasty

AB Tasty

At AB Tasty, we love to help you improve your customers’ experiences – and we are here to do the same for you on the AB Tasty platform! We’re constantly gathering feedback from our users, and next month, you’ll see us roll out our new navigation based on that feedback.

We’re doing this for a few reasons:

  1. We want to give you the best – and that means further improving the quality of your experience on the platform. ?
  2. We want you to be able to find exactly what you need, when you need it – which means improving the organization of information, classifying your favorite (and new!) features in an easy-to-navigate way. ?️
  3. We want you to have the most intuitive experience possible – by providing you with better guidance from the first time you log in and get you from A to B as quick as can be. ?

What does that mean for you?

We’ll guide you through the updates in the coming weeks, but here’s a sneak peek of what to expect:

  1. Better visibility with a new sidebar navigation, allowing you to easily access any area of the platform with a single click – and collapse it for more workspace.

    • We’ve gotten rid of the hamburger menu in favor of giving you more control over where you want to go within the platform – whether it be Tests, Personalization, Audience, Analysis, or ROI – plus a login button to take you directly to Flagship, our feature management solution. ?
  2. Improved access to Settings, reorganized to match our customers’ most-used options.
    • We’ve designed a sleeker look, consolidating settings menu for a cleaner appearance and easier navigation. ?
  3. New header to accompany you through every step of the workflow, from campaign creation to reporting, giving you a better bird’s eye view of a campaign’s status.

    • Your step-by-step buttons will remain exactly where they are, but the header will shift to make everything more easily visible to you – including an editable campaign name, status, and reporting, right alongside the tag and account info. ?

We hope these exciting changes make a big impact on how you use AB Tasty! ?

We know you might have questions as you go through the new navigation, and we are here to help! We also know you might have feedback – about the new design and beyond – and we invite you, as always, to share it with us on our Canny board, accessible via this link.

See you on the new navigation soon!

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Jan 11, 2022
5min read

1,000 Experiments Club: A Conversation With Lukas Vermeer of Vista

AB Tasty

AB Tasty

When it comes to kickstarting experimentation within an organization, Lukas Vermeer recommends starting small and (keeping it) simple.

Lukas Vermeer took this advice to heart when he dove head-first into the world of AI and machine learning during the early stages of its development, when there was little industry demand. Through consulting for various companies, Lukas discovered his ideal work environment: a scale-up, where he could put his data and machine learning expertise to use.

Enter Booking.com. Lukas joined the Dutch digital travel company during the scale-up phase and went on to lead the experimentation team for eight years, scaling the team from three people to 30 people.

Once the experimentation team at Booking.com had reached maturity, he embarked on a new adventure in 2021 as director of experimentation at Vista. He is building and shaping the experimentation culture and tapping into the potential of their data, to further Vista’s impact as an industry leader in design and marketing solutions for small businesses.

Lukas spoke with AB Tasty’s VP of Marketing Marylin Montoya about the process and culture of experimentation; from the methods to the roles of the teams involved within an organization. Here are some of the key insights from their conversation.

Get strategic about experimentation

Knowing the purpose of your experiment is key. Lukas recommends focusing your efforts on testing big features that can drive real change or impact the company’s bottom line, rather than UI design.

Ask yourself, “What are the biggest questions that are driving your business case at the moment? What are the biggest assumptions that are behind your strategic planning?” he says. Rather than increasing the number of experiments, focus on the correct execution of more significant experiments.

When it comes to building a culture of experimentation within an organization, Lukas suggests using the flywheel method. The first experiment should garner attention by splitting the company’s opinion 50/50, as to whether it will work. This demonstrates that it can be hard to predict the success of experiments, thereby underlining the “unquantifiable value of experimentation.” We need to acknowledge that it is equally valuable to avoid shipping a bad product (that could reduce revenue), as it is to figure out strategically what you should invest in going forward.

Structure your organization for experimentation success

The way your business and teams are structured will impact how seamlessly your experiments are executed. Lukas recommends that the product development team take full ownership of the experiments.

The experimentation team should be facilitating experiments by providing the tools, education and troubleshooting support to the product development team, who can then run their experiments autonomously.

By training product managers in the process of experimentation — such as the different tests and tools available, their strengths and weaknesses, the assumptions they make and when to use them — they can work autonomously to test their ideas and select from a portfolio of experimental methods in order to make a decision.

There is, however, a social aspect to experimentation that should not be ignored. Given the subjective nature of data interpretation and analysis, Lukas highlights the importance of discussing the outcomes and giving feedback on the experimentation process in order to optimize it.

“The whole point of an experiment is to (…) drive a decision, and the decision should be supported by the evidence at hand,” Lukas says. Just as scientists peer-review their papers before publishing, experiments using the scientific method should follow the same guidelines to document the hypothesis, method, results and discussion in the reporting. (An opinion that has been echoed by 1,000 Experiments Club podcast guest Jonny Longden.)

The biggest threat to experimentation culture: leadership or roadmaps?

When people in product development talk about “roadmaps,” they’re not actually roadmaps, Lukas says. It’s more of a linear wishlist of steps that they hope will bring them to the goal. The problem is that there’s rarely alternative routes or redirections should they stray from the original plan.

It’s hard to change direction at the first failed experiment, Lukas explains, due to the  “escalation of commitment.” That is, the more time and energy you have invested into something, the more difficult it is to change course.

So, is it time to ditch roadmaps altogether? Lukas advises that roadmaps should simply acknowledge that there is inherent uncertainty. There are many unknowns in product development, and these only become visible once the products are being built and exposed to customers. This is why the build-measure-learn model works, because we take a few steps and then check if we’re heading in the right direction.

Lukas says the goal should not be to “deliver a final product in two months,” rather you should incorporate the uncertainty into the deliverables and word the objective accordingly, for example: to check if customers are responding in the desired way.

What else can you learn from our conversation with Lukas Vermeer?

  • When to start experimenting and how to build a culture of experimentation
  • The importance of autonomy for experimentation teams
  • The three levels of experimentation: method, design, execution
  • How to accelerate the experimentation process
About Lukas Vermeer

Lukas Vermeer is an expert in implementing and scaling experimentation with a background in AI and machine learning. Currently, Lukas is the director of experimentation at Vista. Prior to this, he spent over eight years at Booking.com, from data scientist, product manager to director of experimentation. He continues to offer his expert consulting services to companies that are starting to implement experimentation. His most recently co-authored paper, “It Takes a Flywheel to Fly: Kickstarting and Keeping the A/B Testing Momentum,” helps companies get started and accelerate experimentation using the “investment follows value follows investment” flywheel.

About 1,000 Experiments Club

The 1,000 Experiments Club is an AB Tasty-produced podcast hosted by Marylin Montoya, VP of Marketing at AB Tasty. Join Marylin and the Marketing team as they sit down with the most knowledgeable experts in the world of experimentation to uncover their insights on what it takes to build and run successful experimentation programs.

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Oct 20, 2021
11min read

Net Promoter Score (NPS): Your Ultimate Guide to the What, Why, and How

AB Tasty

AB Tasty

In a world where customers increasingly seek to buy into a brand than buy from a brand, it’s critical that companies create experiences that turn customers into loyal fans, rather than regard them as simple business transactions.

Customer satisfaction alone is no longer enough to thrive in today’s economy. The goal is to earn your customers’ fierce loyalty with authenticity and transparency, while aligning your offers and actions with a mission that speaks to them.

By measuring the net promoter score (NPS), businesses gain unique insight into how consumers perceive their customer journey in a number of different ways. Companies that use NPS to analyze customer feedback and identify areas of improvement hold the keys to optimizing rapid and effective business growth.

In this article, we’ll cover why measuring NPS is essential to scaling business sustainably, how to gather and calculate NPS feedback, and best practices to increase response rates and run successful NPS campaigns.

[toc]

What is NPS?

Let’s start with a little history. The Net Promoter Score was officially pioneered and coined by Fred Reichheld in the early 2000s, and has since become an invaluable methodology for traditional and online businesses alike. The value lies in using data to effectively quantify customer loyalty and its effect on business performance — a factor that was previously challenging to measure at scale.

What is NPS?
(Source)

The system works by asking customers a version of this question: How likely are you to recommend our brand/product/service to a friend or colleague? Answers range on a scale of 0-10, from “not at all likely” to “extremely likely.” Depending on their answers, respondents are separated into one of three categories.

  • Promoters (score 9-10): Loyal customers who keep buying and actively promote and refer your brand to their circle of friends, family, and/or colleagues.
  • Passives (score 7-8): Customers who’ve had satisfactory or standard experiences with your brand, and are susceptible to competitors’ offers.
  • Detractors (score 0-6): Unhappy customers who risk damaging your brand with public complaints and negative word-of-mouth.

To calculate the final net promoter score, subtract the percentage of promoters from the percentage of detractors. The metric can range from a low of -100 to a maximum of 100, the latter if every customer was a promoter.

For many e-commerce companies, high customer retention, referral, and positive reviews are all critical drivers of success. NPS helps these businesses understand overall buyer behaviors and identify which customer profiles have the potential to be brand enthusiasts, enabling marketers to adjust their strategy to convert passives into promoters.

Simply put, NPS surveys are a simple and powerful method for companies to calculate how customer experience management impacts their overall business performance and growth.

How to gather NPS feedback

Common methods used to gather NPS feedback are email, SMS, and website pop-ups or chat boxes. Regardless of which method is used, there is a common set of steps to ensure a successful NPS campaign:

  1. Set clear objectives before sending out the NPS survey. Save time and increase the relevance of survey responses by determining exactly what kind of feedback you’re looking for before launching the survey.
  2. Segment recipients with customer behavior profiles. Get specific with your survey questions by customizing them to different audiences based on their unique history and interaction(s) with your brand.
  3. Make surveys short, concise, and timely. Instead of lengthy annual or quarterly feedback requests, increase response rates by sending quick and easy surveys to customers soon after they’ve had meaningful interactions with your brand.
  4. Use an automation tool to optimize survey delivery. Whether it’s with an email marketing platform or website widget integration, using automation tools to design and deliver your NPS surveys streamlines the entire feedback process, while reducing the margin for human error.

Integrating the NPS survey directly into the customer journey on your website increases response rate and relevancy of feedback. To implement a NPS survey like this, try using an intuitive visual editor like AB Tasty with NPS widget capabilities.

AB Tasty’s visual editor enables marketers of all levels to:

  • Modify visual and interactive elements on the website without any manual coding necessary;
  • Set up action-tracking to directly measure the performance of variations you’ve created;
  • Use the NPS widget to customize the content and feel of surveys across one or more pages of the website; and
  • Track the evolution potential of customer loyalty and benchmark against competitor performance via the NPS report.

Below are two case studies of clients who’ve used the AB Tasty NPS widget with highly successful campaigns to collect customer feedback and gain valuable insight to improve their customer experiences.

How to calculate NPS feedback

So what makes a good NPS score? A general rule of thumb states that anything below 0 means your business has some work to do … and a “good score” falls between 0-30. However, the true value of a NPS score depends on several factors — namely what industry your business is in.

If your NPS score isn’t as high as you’d hoped, don’t fret! There is always room for improvement and the good news is that it’s easy to implement actionable changes to optimize your NPS campaigns, no matter where you are on the scale.

When benchmarking for NPS, look at competitors that are in the same industry and relatively similar size as your company to get the most accurate visualization possible. Look for graphs that map out average NPS data by industry to get more insights on performance and opportunities for improvement in your sector.

It’s important to understand that comparing your business’s results to significantly larger or unrelated brands can lead not only to inaccurate interpretation of the data, but also sets unrealistic and irrelevant goals for customer experience teams.

How to increase your NPS response rate

Reaching your customers with your NPS survey is just one half of the battle. The other half is getting enough customers to actually respond to it, which is critical to calculate an NPS score that accurately reflects your company’s customer satisfaction performance. Here are some tips for boosting your NPS response rate:

  • Customize your NPS survey. Take the time to brand your survey with the proper fonts and colors, following your brand design guide. Given the fact that the average person sees upwards of 6,500 ads in a day, information overload is a real struggle for consumers and marketers alike. A consistent look and feel from your survey helps customers recognize and trust your brand, making it an easy transition to take the next step in their customer journey.
  • Personalize the message. Studies show that personalized subject lines increase email open rates by 26%. If you’re sending the survey in an email, use merge fields or tags to automatically add each recipient’s name into the subject line or body of the email.
  • Use responsive design. 75% of customers complete surveys on their phone. Make sure your survey is fully functional and accessible from all devices (i.e., desktop, mobile, and tablet), as well as on as many operating systems and internet browsers as possible.
  • Offer incentives for completing the survey. From gift cards, cash, and promo codes to raffles, offering monetary rewards is an easy method to increase engagement, especially for longer surveys. However, this should be researched and done carefully to avoid review bias and more seriously, legal issues.

Why you should use NPS

Taking customer feedback seriously is important business. As of 2020, 87% of people read online reviews for local businesses, and 79% said they trust online reviews as much as a personal recommendation from friends or family. This means your customers’ perception of your brand can literally make or break it.

It’s clear that looking at sales revenue as the sole determiner of success is not sustainable for long-term business growth. Neither is assuming that several user case scenarios represent the majority without the data to prove it.

NPS is an especially powerful metric for e-commerce, as it uses data to help businesses identify truly relevant areas for improvement and opportunities to build a strong and loyal customer base that is so vital to thrive in this sector.

Build a strong relationship with your customer base
Building a strong relationship with your customer base and incentivizing brand promoters is crucial to succeeding in the e-commerce market

Rather than guesstimating what priorities should be, businesses can use longer surveys with open-ended questions to evaluate how their customers feel about specific aspects of the business (e.g., products, website, and brand) and target strategy accordingly.

When calculated correctly, NPS is the key to determining the likelihood of repeat business and acquisition driven by brand promoters. Marketing and product teams can boost customer retention and increase sales with customized products they know buyers want. Happy customers love loyalty programs and referral rewards, which also bring in new business with significantly less spend than cold advertising.

When is the ideal time to send users an NPS survey

Deciphering what time customers are most likely to open emails, or when they’re more responsive to brand communications, is one of the biggest challenges for marketing teams.

Some studies suggest that the best time of the week to send emails is Tuesday at 10am. Although as many marketers know from experience, a one-time-fits-all solution doesn’t truly exist (though we wish it did!).

Depending on your industry and audience, your brand’s ideal time to hit send will likely change over time — and experimentation and optimization are the best ways to stay on top of it.

Identify the right time to send customer satisfaction surveys
Identifying the right time to send customer satisfaction surveys requires continual testing of different elements like message personalization and audience segmentation

However it is possible to find ideal times based on data you likely already have: by focusing on meaningful interactions between brand and customer.

One of the optimal times to send a NPS survey is shortly after customers have had a meaningful interaction with the brand. This could be after a customer finishes a purchase cycle, receives a product, or even speaks with customer service.

During this time, the customer experience is still top-of-mind, which means they are more likely to complete a feedback survey with higher chances of providing more detailed — and honest — insights.

It’s also better to send short surveys more frequently. Asking for smaller amounts of feedback more often than once or twice a year enables you to monitor customer satisfaction with a quicker response time.

With regular feedback surveys, businesses can catch onto unhappy customers early on and make prompt changes to address problems in the customer journey, increasing customer retention.

Another benefit of this practice is that businesses can also identify highly successful campaigns throughout the year and prioritize resources on scaling strategies that are already proven to work well.

Do’s and don’ts for running an effective NPS campaign

Do:

  • Add open-ended questions. If you want more qualitative insight to support your business decisions, ask customers for specific input, as Eurosport did in this campaign.
  • Send from a person. Humans value real connections. Increase NPS response rate by sending surveys with the name and email of a real employee, not an automatic “no-reply” bot address.
  • Integrate your NPS survey into the user journey. To boost your reach beyond email surveys, use an NPS widget on your website for increased response rate and in-depth responses. Match your survey’s design to flow with the product page UX.

Don’t:

  • Disrupt the customer journey. Don’t overdo it with pop-up surveys or make them difficult to close, this can distract customers from their website experience and increase bounce rate.
  • Ask only one question. Don’t ask for just a 0-10 score. To collect actionable insight, add a follow-up question after the NPS score to ask why they gave that rating.
  • Not share NPS results. Transparency makes cross-team collaboration more effective and creative. NPS data is valuable for not only customer-facing teams, but also marketing and product teams to improve the customer experience.

Optimize your NPS strategy

In summary, NPS is incredibly user-friendly and simple to implement. This metric helps brands gain actionable insight into their customer loyalty and satisfaction, and identify opportunities to significantly boost customer retention and acquisition.

NPS widgets and automated feedback collection
NPS widgets and automated feedback collection enable cross-team collaborators to work more cohesively on customer experience campaigns

Businesses can use this data to run their operations better and smarter, and also improve cross-team collaboration on enhancing the customer experience. Regular testing and following best practices enable teams to continually improve their NPS strategy and reach higher response rates.

Ready to integrate your next NPS campaign directly into your website and customer journey? With an intuitive interface and no-code visual editor, AB Tasty enables you to fully customize the entire NPS survey live on your website, and experiment with different triggers to optimize your NPS strategy.

Our NPS widget makes it easy to scale this process quickly within even the fastest growing companies — give it a spin today.

AB Tasty’s NPS Widget Case Studies:

  1. How Eurosport’s Survey Pop-In Got 5K Responses in Less Than Two Weeks
  2. Avid Transforms Internal Culture and Website Experience with AB Tasty

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Jul 28, 2021
3min read

Introducing 1,000 Experiments Club: A New Podcast Series From AB Tasty

AB Tasty

AB Tasty

Join VP Marketing Marylin Montoya as she takes a deep dive into all things experimentation

Today, we’re handing over the mic to AB Tasty’s VP Marketing Marylin Montoya to kick off our new podcast series, “1,000 Experiments Club.”

At AB Tasty, we’re a bunch of product designers, software engineers and marketers (aka Magic Makers), working to build a culture of experimentation. We wanted to move beyond the high-level rhetoric of experimentation and look into the nitty gritty building blocks that go into running experimentation programs and digital experiences.

Enter: “1,000 Experiments Club,” the podcast that examines how you can successfully do experimentation at scale. Our podcast brings together a selection of the best and brightest leaders to uncover their insights on how to experiment and how to fail … successfully.

In each episode, Marylin sits down to interview our guests from tech giants, hyper-growth startups and consulting agencies — each with their own unique view on how they’ve made experimentation the bedrock of their growth strategies.

You’ll learn about why failing is part of the process, how to turn metrics into your trustworthy allies, how to adapt experimentation to your company size, and how to get management buy-in if you’re just starting out. Our podcast is for CRO experts, product managers, software engineers; there’s something for everyone, no matter where you fall on the maturity model of experimentation!

We are kicking things off with three episodes, each guest documenting their journey of where they went wrong, but also the triumphs they’ve picked up from decades of experimentation, optimization and product development.

Ronny Kohavi (ex-Amazon, Airbnb, Microsoft) 

He shares a humbling reality check: Most ideas will fail 

Chad Sanderson (Convoy)

He breaks down the most successful types of experimentations 

Jonny Longden (Journey Further)

He believes anyone can and should do experimentation

In the culture of experimentation, there’s no such thing as a “failed” experiment: Every test is an opportunity to learn and build toward newer and better ideas. So have a listen and subscribe to “1,000 Experiments Club” on Apple Podcasts, Spotify or wherever you get your podcasts.

Take to me to the podcast!

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