Building a great website is, unfortunately, not simply a matter of following best practices. Even within a single industry, users will hold varied expectations based on your brand, communication style, target audience, funnel, etc. And while browsing the same website, users’ expectations can vary, with some knowing exactly what they want and others needing to explore, check your returns policy, learn about your sustainability initiatives, and so on.

We have all heard the hype about how AI has been revolutionizing how marketers approach experimentation. Generative AI offers new opportunities for optimizing every aspect of the user journey, allowing marketers to:

• streamline testing,
• create new online experiences, 
• and create new types of user segments for more precise personalized experiences that drive conversions.

This guest blog post was written by Rodolphe Dougoud, Project Lead at fifty-five—a leading data company that helps brands harness the potential of Generative AI and mitigate associated risks effectively with a comprehensive and pragmatic AI strategy, among other services. 

Below, we’ll explore these three perspectives in depth, with real-life examples gleaned from AB Tasty’s new algorithm, Emotions AI, and fifty-five’s work with its clients around GenAI. 

AI in Action for Experiences that Matter

1. Streamline testing

When thinking about A/B testing, you might immediately picture creating an experiment and launching it live on a website. However, the most time-consuming phases of the A/B testing process generally come before and after that: finding new features to try out in order to create a testing roadmap and analyzing the results of these tests. Here, AI can increase test velocity by helping to reduce bottlenecks hindering both of the aforementioned stages.

Test ideation

Your roadmap must not only be top-down but also bottom-up: pay close attention to insights from your UX designers, based on benchmarks from your competitors and industry trends, and data-driven insights based on your own analytics data. Here, AI can facilitate the process by analyzing large datasets (e.g., on-site Analytics data) to find insights humans might have missed.

Result analysis

Similarly, it’s essential to analyze the results of your tests thoroughly. Looking at one KPI can sometimes be enough, but it often represents only one part of a bigger story. An aptly-calibrated AI model can find hidden insights within your testing results. 

While we generally know what data we want to access, the actual querying of that data can be time-consuming. Applying a GenAI model to your dataset can also allow you to query your data in natural language, letting the model pull the data for you, run the query, and create instant visualizations for major time gains.

Content creation

While not necessary for most tests, creating new content to be included in the testing phase can take a long time and impact your roadmap. While GenAI cannot produce the same quality of content as your UX team, a UX designer equipped with a GenAI tool can create more content faster. The model used can be trained with your design chart to ensure it integrates with the rest of your content. Overall, adding a GenAI tool as a complement to your design arsenal can yield substantial gains in productivity and, therefore, reinforce your testing roadmap timeline.

2. Create new online experiences

Marketers should not hesitate to experiment with AI to create unique and interactive experiences. Generative AI can create personalized content and recommendations that can engage users more effectively. 

Consider, for instance, fifty-five’s recent work with Chronodrive, a grocery shopping and delivery app. We used AI to address a common user challenge (and, frankly, near-universal issue): deciding what to make for dinner. 

With our innovative solution, taking a picture of the inside of your fridge will allow the app to create a recipe based on the ingredients it identifies, while a photo of a dish – taken at a restaurant or even downloaded from social media – will generate a recipe for said dish and its associated shopping list. 

 Artificial Intelligence opens new creative options that weren’t available with previous LLM models. Chronodrive’s solution may not be applicable to most companies, but every business can think back on their typical user’s pain points and conceptualize how GenAI could help ease them.

3. Create new types of user segments for more precise personalized experiences

When a customer enters a store, a salesperson can instantly personalize their experience by checking if they want to be helped or just want to browse, if they are discovering the brand or are already sold on it, if they require guidance or know precisely what they want… A website, on the other hand, necessitates extra effort to present the user with a similarly personalized experience. 

Online, segmentation thus becomes indispensable to deliver the most satisfying user experience possible. Even during testing phases, deploying A/B tests on user segments makes achieving significant results more likely, as increased precision helps mitigate the risk of obtaining neutral results.

AI can analyze a wide array of user interactions on a given website to determine which elements drive the most conversions, or how different users respond to specific stimuli. This analysis can allow brands to classify users into new segments that could not have been available otherwise. For instance, fifty-five applied AI to split Shiseido’s website users between low and high-lifetime value segments. This allowed Shiseido to run differentiated A/B tests and personalize their website depending on the expected lifetime value of the user, resulting in a 12.6% increase in conversions.

Going even further, what if AI could read your emotions? AB Tasty’s new AI algorithm, Emotions AI, can automatically segment your audience into 10 categories based on emotional needs. 

• If a user needs to be reassured, the website can emphasize its free return policy
• If they need clarity, the website can highlight factual information about your product
• And if they need immediacy, the website can hide any unnecessary information to instead focus on its main CTAs

The model estimates the needs of the user by taking into consideration all of their interactions with the website: how long they wait before clicking, whether they scroll through an entire page, where their mouse hovers, how many times they click, etc. This enables stronger personalization, both during testing phases and when deploying online features, by letting you know exactly what your users need. 

Want to Learn More?

If you would like to dive deeper into current experimentation trends, watch our webinar replay here, where fifty-five and AB Tasty explored key CRO case studies and more. And if you have any questions or insights you’d like to share, please leave a comment – we would love to hear from you! 

The post From Clicks to Connections: How AI is Shaping the Future of Digital Optimization appeared first on abtasty.

In this article, you will discover the different forms of virtual shopping assistants available in e-commerce and the advantages they bring to you and your customers.

What are virtual shopping assistants?

Virtual shopping assistants, enabled by shopping engagement software, provide your shoppers with support in their product selection through an interactive and personalized exchange. By asking precise questions, your customers can find products that align with their wishes and needs more quickly.

This approach is based on the purchase advice provided in brick-and-mortar retail, aiming to overcome the impersonal components of online shops and enhance the individual user experience.

How do virtual shopping assistants differ from faceted search?

With faceted search, your customers can filter their search results in the online shop to view the products that interest them. For example, when searching through an e-commerce apparel shop they can use faceted navigation to select features, such as women’s blue capris in size 40, providing a user-friendly experience.

However, customers need to already know exactly what they want to buy to filter accordingly. If a customer is uncertain about their purchase or unsure about the specific product features they desire, they require support in the form of virtual shopping assistants.

What kinds of virtual shopping assistants are available?

There are various formats of virtual shopping assistants in e-commerce that can be integrated at different points of the customer journey. Let’s take a closer look at two categories: person-to-person communication tools and automated tools that can handle multiple customer inquiries in real time.

Virtual shopping assistants with human-to-human communication

Below, we present two examples of virtual shopping assistants that utilize human-to-human communication:

Live chat

Live chat is a messenger tool that allows your customers to directly contact an employee of your online shop. Typically integrated as a pop-up window on the company website, it facilitates one-to-one communication, resembling the experience of brick-and-mortar retail.

Video consultation

Video consultation is a rising trend in the e-commerce industry. 

Customers visiting your e-commerce site may still be exploring their needs, making phone, chat or email interactions insufficient. With video consulting, customers can engage in face-to-face conversations with an employee of your online shop, ask questions, and receive individual advice on your products and processes. 

For instance, customers can share their screens and present their ideas and inspiration to the sales representative, leading to a more targeted sales pitch. This combination of online shopping with personalized attention replicates the experience of boutique purchases and ultimately boosts customer loyalty and satisfaction. 

The advantage: Your customers receive immediate, personalized answers to their questions about products and processes while they browse your shop. Especially for complex products that require explanation, customer-oriented live chat can positively influence purchase decisions. Additionally, you can offer appointments for individual purchase advice.

Virtual shopping assistants with AI-based tools

Now, let’s explore two examples of online consulting software that utilize AI-based tools for real-time interactions with multiple customers at once.

AI-based chatbots

Chatbots using artificial intelligence can respond to hundreds of customer inquiries simultaneously and in real time. 

With the emergence of large language model chatbots such as OpenAI’s ChatGPT and Google’s Bard, brands have the potential to revolutionize how they engage with their customers online.

Depending on how the tool is programmed, it can recognize natural language, generate suitable answers from text blocks and databases on your website, and even escalate queries to a human employee if necessary. This enables personnel-friendly automation of various processes. 

Guided Selling

Guided Selling involves guiding your customers through the product selection process to facilitate a confident purchase decision. This is particularly useful for potential buyers who may not possess enough knowledge about the products to make an informed choice.

For instance, when it comes to purchasing a stroller, expectant parents can feel overwhelmed by the countless models available. Guided Selling assists them in narrowing down the selection through targeted questions, leading to the ideal stroller. This can be seen in the example from babymarkt.de, who uses Guided Selling from AB Tasty to provide better shopping experiences for their customers.

This form of assistance, where a customer is guided step-by-step through the consultation process based on specific questions, is especially suitable for products that require explanation and mirrors the experience of a sales pitch in brick-and-mortar retail. Guided Selling can also be used for self-explanatory products, where customers can find the right product selection by selecting certain tags.

What makes Guided Selling special is that the results can be personalized to display suitable products based on the individual click and buying behavior of your customer. This ensures that your customer receives not only products that match their desired features and requirements but also their unique preferences.

Why is good customer engagement important in e-commerce?

Customers who feel well-advised are happy to come back. This applies to both brick-and-mortar stores and e-commerce shops. In addition, there are other reasons for using shopping engagement software like virtual shopping assistants.

Personalized shopping experience

When potential buyers walk into a brick-and-mortar store, they can approach the on-site sales consultants to find the right product. 

By integrating this service into your online shop in the form of live chats, video advice or Guided Selling, you enable your customers to recreate the feeling of an interactive, personalized shopping experience.

Shoppers become customers

Virtual shopping assistants help you convert potential buyers into customers. By putting customers in direct contact with your team or catalog, they get answers to their questions that can positively influence their purchase decision. 

For very personal products such as mattresses, a virtual shopping assistant tool helps visitors to find the one that exactly meets their needs from the multitude of models. 

A better user experience

Your visitors appreciate positive experiences throughout their customer journey. 

Support through virtual shopping assistants gives them a secure feeling when choosing a product and more frequently leads to a purchase decision. In addition, virtual shopping assistants make shopping easier: You present your customers with suitable solutions, they feel understood and the positive user experience is anchored in their memory.

Higher conversion

With virtual shopping assistants and shopper engagement software, you can reduce lost sales opportunities and thus increase your conversions. Sometimes potential buyers leave a shop because they didn’t find a product that is actually there. If they can easily ask a sales representative about the product via live chat, it will improve their shopping experience.

Your potential customers have already added products to their shopping cart, so why are they abandoning the checkout process? One possible reason: They had a question about a process that was not answered quickly enough. With an AI-based chatbot available during the checkout, these questions can be solved quickly and efficiently.

Higher customer satisfaction

The personalized service of a virtual shopping assistant creates an intimate atmosphere – a 1:1 exchange reminiscent of brick-and-mortar experiences. This not only strengthens potential buyers’ trust in your company but also their satisfaction. And satisfied customers turn into loyal customers. 

Fewer Returns

Implementing virtual shopping assistants in your shop reduces the risk of returns. The two most common reasons for returns are either that the product didn’t fit or they didn’t like it. 

With personal, targeted advice, you can help your customers to choose the right products that meet their wishes and needs as precisely as possible. This reduces your costs and makes your returns management easier.

Conclusion: Virtual shopping assistants make e-commerce more human

Virtual shopping assistants are a must-have in e-commerce. It offers advantages for you as an e-commerce marketer as well as for your customers. 

Live chats or chatbots, video advice and Guided Selling make it easier for potential buyers to select a product and improve their user experience. In a 1:1 exchange, they receive personalized answers to their questions – the online shop becomes more human. At the same time, you benefit from higher customer loyalty and fewer returns, which means you can increase your sales.

The post Understanding shopping engagement software: How do virtual shopping assistants work? appeared first on abtasty.

This webinar goes into detail on the importance of personalization, practical steps you can take to make your customers known, the most highly valued segments you need to target, and ways in which experimentation can help you do this.

We look into how emotions play their part in customer decisions and how you can use AI to adapt your messages, experiment with unique personalized messages for each visitor type, delve into data to understand their needs, conduct tests to identify effective messaging, and construct personalized journeys targeting specific emotional needs.

We discuss:

• Personalizing the customer journey
• Understand the emotional needs of audiences to bolster their Experience
• Have more winning variations by digging deeper into what works and for which type of personality with analytics

The post Enhance Your Personalization With AI appeared first on abtasty.

Since OpenAI launched its own form of generative AI, ChatGPT, in November 2022, the world has yet to stop talking about its striking capabilities. It’s particularly fascinating to see just how easy it is to get results after interacting with this bot which is comprised of deep-learning algorithms for natural language processing.

Even Google quickly followed by launching a new and experimental project, Gemini, to revolutionize its own Search. By harnessing the power of generative AI and the capacity of large language models, Google is seeking to take its search process to the next level.

Given the rapid growth of this technological advancement over the past few months, it’s time that we talk about generative AI in the context of A/B testing and experimentation.

Whether you’re curious about how AI can impact your experiments or are ready for inspiration we’ll discuss some of our ideas around using AI for A/B testing, personalization, and conversion rate optimization.

What is generative AI?

Generative AI is a type of artificial intelligence that doesn’t have programming limitations, which allows it to generate new content (think ChatGPT). Instead of following a specific, pre-existing dataset, generative AI learns from indexing extensive data, focusing on patterns and using deep learning techniques and neural networks to create human-like content based on its learnings.

The way algorithms capture ideas is similar to how humans gather inspiration from previous experiences to create something unique. Based on the large amounts of data used to craft generative AI’s learning abilities, it’s capable of outputting high-quality responses that are similar to what a human would create.

However, some concerns need to be addressed:

• Biased information: Artificial intelligence is only as good as the datasets used to train it. Therefore if the data used to train it has biases, it may create “ideas” that are equally biased or flawed.
• Spreading misinformation: There are many concerns about the ethics of generative AI and sharing information directly from it. It’s best practice to fact-check any content written by AI to avoid putting out false or misleading information.
• Content ownership: Since content generated with AI is not generated by a human, can you ethically can claim it as your own idea? In a similar sense, the same idea could potentially be generated elsewhere by using a similar prompt. Copywriting and ownership are then called into question here.
• Data and privacy: Data privacy is always a top-of-mind concern. With the new capabilities of artificial intelligence, data handling becomes even more challenging. It’s always best practice to avoid using sensitive information with any form of generative AI.

By keeping these limitations in mind, generative AI has the potential to streamline processes and revolutionize the way we work – just as technology has always done in the past.

10 generative AI uses for A/B testing

In the A/B testing world, we are very interested in how one can harness these technological breakthroughs for experimentation. We are brainstorming a few approaches to re-imagine the process of revolutionizing digital customer experiences to ultimately save time and resources.

Just like everyone else, we started to wonder how generative AI could impact the world of experimentation and our customers. Here are some ideas, some of them concrete and some more abstract, as to how artificial intelligence could help our industry:

DISCLAIMER: Before uploading information into any AI platform, ensure that you understand their privacy and security practices. While AI models strive to maintain a privacy standard, there’s always the risk of data breaches. Always protect your confidential information. 

1. Homepage optimization

Your homepage is likely the first thing your visitors will see so optimization is key to staying ahead of your competitors. If you want a quick comparison of content on your homepage versus your competitors, you can feed this information into generative AI to give it a basis for understanding. Once your AI is loaded with information about your competitors, you can ask for a list of best practices to employ to make new tests for your own website.

2.  Analyze experimentation results

Reporting and analyzing are crucial to progressing on your experimentation roadmap, but it’s also time-consuming. By collecting a summary of testing logs, generative AI can help highlight important findings, summarize your results, and potentially even suggest future steps. Ideally, you can feed your A/B test hypothesis as well as the results to show your thought process and organization. After it recognizes this specific thought process and desired results, it could aid in generating new test hypotheses or suggestions.

3. Recommend optimization barriers

Generative AI can help you prioritize your efforts and identify the most impactful barriers to your conversion rate. Uploading your nonsensitive website performance data gathered from your analytics platforms can give AI the insight it needs into your performance. Whether it suggests that you update your title tags or compress images on your homepage, AI can quickly spot where you have the biggest drop-offs to suggest areas for optimization.

4. Client reviews

User feedback is your own treasure trove of information for optimization. One of the great benefits of AI that we already see is that it can understand large amounts of data quickly and summarize it. By uploading client reviews, surveys and other consumer feedback into the database, generative AI can assist you in creating detailed summaries of your users’ pain points, preferences and levels of satisfaction. The more detailed your reviews – the better the analysis will be.

5. Chatbots

Chatbots are a popular way to communicate with website visitors. As generative AI is a large language model, it can quickly generate conversational scripts, prompts and responses to reduce your brainstorming time. You can also use AI to filter and analyze conversations that your chatbot is already having to determine if there are gaps in the conversation or ways to enhance its interaction with customers.

6. Translation

Language barriers can limit a brand that has a presence in multiple regions. Whether you need translations for your chatbot conversations, CTAs or longer form copy, generative AI can provide you with translations in real time to save you time and make your content accessible to all zones touched by your brand.

7. Google Adwords

Speed up brainstorming sessions by using generative AI to experiment with different copy variations. Based on the prompts you provide, AI can provide you with a series of ideas for targeting keywords and creating copy with a particular tone of voice to use with Google Adwords. Caution: be sure to double-check all keywords proposed to verify their intent. 

8. Personalization

Personalized content can be scaled at speed by leveraging artificial intelligence to produce variations of the same messages. By customizing your copy, recommendations, product suggestions and other messages based on past user interactions and consumer demographics, you can significantly boost your digital consumer engagement.

9. Product Descriptions

Finding the best wording to describe why your product is worth purchasing may be a challenge. With generative AI, you can get more ambitious with your product descriptions by testing out different variations of copy to see which version is the most promising for your visitors.

10. Predict User Behavior

Based on historical data from your user behavior, generative AI can predict behavior that can help you to anticipate your next A/B test. Tailoring your tests according to patterns and trends in user interaction can help you conduct better experiments. It’s important to note that predictions will be limited to patterns interpreted by past customer data collected and uploaded. Using generative AI is better when it’s used as a tool to guide you in your decision-making process rather than to be the deciding force alone.

The extensive use of artificial intelligence is a new and fast-evolving subject in the tech world. If you want to leverage it in the future, you need to start familiarizing yourself with its capabilities.

Keep in mind that it’s important to verify the facts and information AI generates just as you carefully verify data before you upload. Using generative AI in conjunction with your internal experts and team resources can assist in improving ideation and efficiency. However, the quality of the output from generative AI is only as good as what you put in.

Is generative AI a source of competitive advantage in A/B testing?

The great news is that this technology is accessible to everyone – from big industry leaders like Google to start-ups with a limited budget. However, the not-so-great news is that this is available to everyone. In other words, generative AI is not necessarily a source of competitive advantage.

Technology existing by itself does not create more value for a business. Rather, it’s the people driving the technology who are creating value by leveraging it in combination with their own industry-specific knowledge, past experiences, data collection and interpretation capabilities and understanding of customer needs and pain points.

While we aren’t here to say that generative AI is a replacement for human-generated ideas, this technology can definitely be used to complement and amplify your already-existing skills.

Leveraging generative AI in A/B testing

From education to copywriting or coding – all industries are starting to see the impact that these new software developments will have. Leveraging “large language models” is becoming increasingly popular as these algorithms can generate ideas, summarize long forms of text, provide insights and even translate in real-time.

Proper experimentation and A/B testing are at the core of engaging your audience, however, these practices can take a lot of time and resources to accomplish successfully. If generative AI can offer you ways to save time and streamline your processes, it might be time to use it as your not-so-secret weapon. In today’s competitive digital environment, continually enhancing your online presence should be at the top of your mind.

Want to start optimizing your website? AB Tasty is the best-in-class experience optimization platform that empowers you to create a richer digital experience – fast. From experimentation to personalization, this solution can help you activate and engage your audience to boost your conversions.

The post 10 Generative AI Ideas for Your Experimentation Roadmap appeared first on abtasty.

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.

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.

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.

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

2. 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 delivered a customer experience on par with their clients’ expectations (Source)
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3. 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 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 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 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.

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.

The post The Rise of the Experience Economy and How It’s Shaping the Future of E-Commerce appeared first on abtasty.

The Cosmetics Industry is valued at $532 billion. It’s an industry that appears to remain constant even in the face of disruption (the so-called “Lipstick Effect” helping secure its reputation as being “recession proof”). This report takes a closer look at the trends shaping and elevating the Cosmetics Industry, from the influence of digitally native brands to how artificial intelligence is shaping everything from product formulas to hyper-personalized customer experiences.

Challenge

How is the Cosmetics Industry adapting in the face of unprecedented digital advancements and the global disruption of AI?

What you’ll learn

• The link between conscious consumerism and cosmetics
• The relationship between digitally native brands and large corporations
• How artificial intelligence is helping create highly personalized experiences

The post Cosmetics & Consumer Behavior: A Global Industry Report appeared first on abtasty.

Situation

No one likes being put on hold—especially when you’re trying to reach customer support with a question related to your livelihood (like insurance or wealth management). So, Generali decided to streamline the entire process.

The goal was to help visitors more readily find the information they needed on Generali’s website and curb calls to customer support (particularly for questions that could more easily be answered online). This way, Generali’s customer support team would have the increased bandwidth needed to help individuals with complex questions.

Generali developed a chatbot that was able to interact with visitors on its site by answering basic questions and highlighting relevant insurance offers. If there was a question the bot couldn’t answer, it would connect users to the appropriate Generali agent directly.

The Generali team had tested various names and avatars for its bot among a small pool of clients before ultimately settling on ‘Leo.’

Then, Generali worked with AB Tasty to integrate Leo into its website and track performance.

Campaign

AB Tasty Technical Solution Engineers were able to write the JavaScript and CSS code needed to trigger Leo on desktop devices. Data was then collected in real-time (in the AB Tasty platform) to track Leo’s engagement rates and highlight how visitors interacted with the chatbot during a 6-month period.

Generali also used AB Tasty’s visual editor to quickly make cosmetic changes to the site and measure the impact of these modifications on Leo’s performance.

Results

Leo was clearly a hit with Generali’s clients. At the end of the campaign, there were 100,000 recorded interactions with Leo on the website and more than 2,400 calls avoided, giving Generali the reassurance they needed to integrate the chatbot on mobile and tablet devices.

These high engagement rates, and reduced customer support wait times, proved Leo’s positive impact on the user experience. This campaign also provided a benchmark for evaluating Leo’s ongoing performance—which is essential for continuous optimization.

Currently, interactions with Leo are averaging 800 conversations a day.

Takeaway Tip

Chatbots have the potential to streamline customer support and enhance user experiences—when implemented strategically. As Generali shows, simply integrating a chatbot into your site isn’t enough. You need to set performance goals, collect analytics and track engagement to understand how visitors use this feature. With AB Tasty, Generali was able to easily modify their interface and collect data on Leo’s performance to know with certainty that it benefited the user experience.

This campaign also points to the ways in which artificial intelligence can increase the efficiency of human operations. Leo wasn’t created to take the place of customer support representatives, but to help them by handling straightforward tasks so team members could focus on more complex, higher-level questions.

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