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The University of Helsinki ensures better customer experiences through AI-driven personalization

The University of Helsinki is Finland’s largest and oldest academic institution. Since 1640, it has contributed to the establishment of a fair and equal society that is considered the best in the world according to a number of indicators. The figures are impressive: 40,000 students and employees; 50,000 web pages; and 3M monthly page loads. 

In the international Webometrics ranking for online visibility, the university placed among the top 10 universities in Europe and the top 60 universities in the world. It’s great evidence of the data-driven approach and level of high ambition in creating exceptional customer experience across all their online services. 

Their website helsinki.fi provides information on nearly 100 degree-programs as well as doctoral education and lifelong learning opportunities. The website offers content for many other groups also; international academia, researchers, alumni, university funders, business, and political decision-makers, journalists, and citizens who are interested in science. The pages offer research information, latest news, and cooperation opportunities for all friends of research and science.

The university website is run much like a big media house with tens of different interest groups and thousands of articles. The online communications team at the University understood that a static website that looks the same for everybody is not the modern way of serving different interest groups. They believe that website personalization is the way forward to create better customer experiences. 

Frosmo’s personalization software was chosen to replace the competitor technology during fall 2019. The university uses Frosmo personalization software to create customer journeys with personalized hero banners, A/B testing, and recommendations that use NLP (Natural Language Processing).  

Clear KPIs are set for personalization, increased click-through rate (CTR), better customer experience with better website usability, and personalized content as well as better content discoverability. A/B testing enables data-driven decision-making and it’s been part of the university’s way of doing for many years.

“We see website personalization as the way to provide the best possible web experience to all of the University of Helsinki target audiences. It also strengthens our efforts for true data-driven service development.”

Anni Aarinen
, Head of Development, Digital Content, University of Helsinki

 

AI-driven NLP for better content discoverability and great customer experiences

One of the most important functions of the university is to produce reliable information for the whole society and the news and articles have a wide audience among “regular” citizens. The core of good customer experience is great content discoverability. AI-driven NLP is the best option to cater to the needs of many target groups by recommending articles according to the interests of the reader.

NLP at Helsinki University website

The Frosmo NLP algorithm gathers insights from all the articles of the university by analyzing the text, titles, lead paragraph, and scoring the articles for similarity, and then ranks them in order of relevance.

Recommendations at Helsinki University website
Recommendations at Helsinki University website

The CTR is an important metric to indicate the relevancy of the articles that NLP recommends and how many clicks the recommended articles get. The results have been great and more than 25% of the users who have seen article recommendations have clicked them.

Semantic relationships of words are handled by Fasttext incorporated with Frosmo’s algorithms to give the best articles similarity.

 

Data-driven website management through A/B testing

The usability and whole customer experience on a website this big are really important. It’s next to impossible to make good decisions without testing and adopting the best performing versions. A/B testing is widely used in testing new web designs, the order of content listings, different titles, and texts.

It’s fascinating to test larger implications of the new designs on the website, for example, to test whether the size of a picture has an effect on the scroll depth. Frosmo A/B testing is able to give us more in-depth data on web behavior than we would get from Google Analytics. Testing is part of our core and will definitely play a big part in gathering data for our new website design project.

Anni Aarinen, Head of Development, Digital Content, University of Helsinki

 

Interested in website personalization and how to drive data-driven culture?
Request a demo

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How AI-driven personalization and human creativity make a winning pair

Artificial Intelligence (AI) provides opportunities for augmenting human creativity. You can now design campaigns that deliver the right experience in the right place and at the right time. Combining machine-driven analytics and human creativity holds the key to creating the best possible customer experience. The huge benefits from this collaboration mean value for businesses — more revenues, more profitability.

 

The power of the human mind and creativity

Machine learning is going to change every single aspect of technology, but no machine will be able to mimic the creative ability of the human mind.”
Shantanu Narayen
CEO, Adobe

When we imagine an AI-powered future, our biggest fear is dehumanization. New technologies have already revolutionized and disrupted digital marketing in many ways, and marketers sometimes worry that AI will eventually replace them. But even though AI can enable dynamic optimization and powerful personalization, it has limited capacity to create new ideas that truly resonate. The reason is simple — most of the best theories start from human experiences, past scenarios, and observations.

There will always be a need for intuition, which is largely part of the human creative process. Humans are way better at responding to extreme situations or unpredictable scenarios. Therefore, even at its most powerful, AI won’t replace human intelligence and creativity any time soon. It’s only by maintaining the human touch that AI can add value to businesses.

Humans have contextual information when reading results from machines, achieved by vast experiences with customers, understanding human behavior, familiarity with time-related insights such as seasonal events, holidays, festivals, and trends in the market as well as macro-economic information. For instance, a customer looking for a particular pair of shoes in your ecommerce store starts a conversation with a chatbot which immediately presents her with a range of available items and other options based on the description given and her previous shopping history. When the item was placed in the shopping cart, the chatbot tells her of a personal discount because of her nth time store visit and then offers some personalized recommendations for complementary items. 

Everything is going smoothly and the conversation is as human as possible when the customer suddenly asks a question about the store’s plans to have some items related to the upcoming Olympic Games. The event is in less than a year’s time and the customer wants to have a pair of shoes with the logo. The chatbot will find this too complex because it hasn’t been programmed into the system yet, so it passes the chat session seamlessly to a live agent who resolves the query. Algorithms are great at optimization and automation but have restrictions on interpreting findings held up against possible outcomes based on context.

AI helps you to get things done faster and more efficiently. It also opens the door to new and exciting ways to experiment, test, and learn from data to create better and improved customer experiences. But it’s essential that brands keep using the human touch to fully understand the nuances of human behavior.

 

Embracing the magic of AI-driven personalization

Customers have learned to expect personalized messages and offers delivered in every stage of their shopping journey, and they won’t settle for anything less. Their needs and preferences change all the time. By leveraging the power of AI, it’s easy to gather in-the-moment insights that are critical in predicting what customers want. AI helps create and deliver tailored customer experiences more effectively and transparently through highly targeted content. 

The problem with merely relying on gut feeling is that it doesn’t have numbers to back it up. That’s when data becomes crucial. For example, AI provides a careful analysis of your consumer’s past buying behavior hence giving you the opportunity to customize the way your ecommerce homepage should look and what products your customer should see. Instead of using an image that you prefer and feel would work, the AI-powered engine creates a dynamic website personalization that leads to higher conversions and greater customer retention with minimal effort. Machine learning does not hamper human intuition, but it can help differentiate between an inspired idea and a bad hunch.

Humans and machines can complement each other resulting in increasing productivity. This collaboration could increase revenue by 38 percent by 2022.
Accenture

In marketing, it’s already common to drive personalization programs or to enable predictive analytics. One of the greatest benefits of AI, however, is the ability to carry the workload and free up human time. Machine learning provides valuable insights on the behavioral patterns of the user base which help make business decisions. Because of automation, people get more time for strategic thinking and planning. With AI, it’s easier to scale, test, measure, and harness ideas, and instantly produce hundreds of iterations — something that would take ages for a human to do.

 

The dynamic duo: When AI gets creative

Data and tech only really fly when human thinking and vision are brought to bear on it.”
Paul Hughes, Founding Partner, and Strategist
Rothco (part of Accenture)

Marketing magic begins with technology-driven insights that enhance human creativity. When AI is done right, it can amplify and enhance human productivity, and open an exciting world of new possibilities. The idea is for humans to drive technology and for machine learning to heighten the capabilities of humans. 

AI can be used to validate and improve ideas by ensuring social relevance, while its human counterpart ensures that the idea retains its emotional resonance. This fusion drives business impact and marketing excellence. It’s a match made in heaven that can produce great results. But getting the most out of it requires good people and good tools.

For example, email marketing click-through rates can be hiked by over 50 % by using machine learning-based tools along with human intuition. Based on real-time user behavior and collected data, an AI model automatically pitches in a personalized message into the marketing content for each user, resulting in a higher click-through and open rate. Consequently, being informed about click-through patterns can help optimize future campaigns. Machine learning makes it possible with minimal effort and maximum accuracy.

AI can do its magic, but it needs to complement human intuition and creativity to reduce limitations and gain a higher level of control that lets you shape algorithm-based decisions and inform future activities. According to McKinsey, AI and machine learning will contribute a staggering USD 2.6 trillion in marketing and sales by 2020.

 

Enable human-centered, AI-powered personalization

Personalization should bring together interpersonal interaction and collective intelligence so connections become faster and computers smarter and more efficient. Human-centered, AI-powered personalization brings together human-curated signals and adaptive machine learning solutions. As a result, systems mature by learning from individual interactions and collective insights. In this way, humans have the ability to outplay certain limitations and restrictions posed by algorithms.

By 2020, businesses that use AI and related technologies like machine learning and deep learning to uncover new insights will take $1.2 trillion each year from competitors that don’t.
-Forrester

The intelligent insights are used in product and content recommendations to better engage customers, improve overall satisfaction, enhance customer experience, and encourage loyalty. And although AI helps optimize customer journeys and make better predictions on what is most likely to sell, human intervention is still critical and relevant, especially in some unexpected scenarios.

Let’s say that three customers buy a TV and a kids’ My Little Pony shirt in an ecommerce store. The machine algorithms interpret this as common behavior, and end up recommending My Little Pony shirts every time a user purchases a TV. But a human brain will be able to identify these unusual situations and make decisions accordingly, for example isolating some categories or subcategories for smarter recommendations.

At the same time, when it comes to testing, traditional methods such as multi-armed bandit are effective in test automation, but there are limitations. You need to test multiple content variations but when there’s a variation that’s constantly failing, the machine won’t be able to create new content to automatically replace it. Only a human can see these failures and come up with new content to test. So, even in test automation, the killer combo is machine automation combined with the logical thinking of humans.

At Frosmo, even though we’re continuously developing our platform’s AI capabilities, we know that human creativity is still the beating heart and the focal point of our product vision. When combined with the proper use of AI, these two make the perfect winning pair.

The idea is to not replace good human intuition, but use smart technologies to facilitate the inception and development of creative ideas that will enhance and further improve marketing efforts and strategies.

 

Download the personalization ebook for some insights, examples, and practical tips for different industries, such as retail, media, and iGaming.

personalization ebook


About the writer:

Tiina Krokfors is a multilingual ecommerce/SaaS professional with experience supporting international clients in a variety of business sectors. Her degree in Engineering and experience in front-end development allows her to combine deep-seated technical knowledge with a value-based approach to customer success. The biggest motivators for her are translating business strategies into innovative and intelligent digital solutions and delighting customers.

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9 personalization trends to keep an eye on in 2020

Growing your ecommerce business faster than the market is not an easy feat. Heavy investments to customer acquisition might be irrelevant if your service is not living up to the promises and standards that are set by the best at the market. However, the opportunities are out there: the internet is full of ecommerce sites that are just simply bad or close to horrible. Either there’s a new site with a “fantastic” fresh look that is missing key usability features or there’s an old-school site that makes you almost sick just by looking at it.

This is the opportunity to grow your market share. Simply put: the better your service delivers, the more you can also invest in customer acquisition. The fastest and most effective marketing investment is to invest in personalization. With personalization, you’ll grow your service revenue and customer lifetime value. That is because, with personalization, you can drastically improve your site usability for each and every customer.

Here are some personalization tips and trends in 2020 to help you stay ahead of the competition:

1. Balancing personalization with data privacy
Although more and more customers are willing to exchange data for convenience and more differentiated experiences, organizations will need to start finding the balance between personalization and privacy. Making the most of personalization doesn’t only entail serving compelling and relevant content. The key is to create great customer experiences through the customers’ shared preferences while still respecting data privacy regulations, safeguarding customer data beyond mere compliance, and ensuring that processes are more transparent.

2. Marketing teams will evolve and will start innovating customer journeys across all touchpoints
As customer experience overtakes price and product as the key brand differentiator, companies expect CMO’s (Chief Marketing Officers) to take advantage of new technologies to drive growth. Because of this, marketing teams will continue to evolve toward delivering world-class customer experiences.

Personalization continues to dominate the ecommerce industry so the marketing roles will become the key to creating innovative customer experiences to pave the way to driving and growing revenue streams. To achieve this goal, marketers and data scientists will collaborate and form a cohesive data-empowered team to innovate customer journeys and orchestrate engagement across all touchpoints.

3. Irrelevant digital advertising will decline
Gone are the days of irrelevant, annoying, and intrusive digital ads. Customers become more engaged with brands through a multitude of channels so they prefer ads custom-made to their interests and tailored to their preferences and recent behaviors.

More than ever, the pressure is on for marketers to truly innovate customer experiences even for first-time website visitors. Relevant and personal messages that cater to customer needs must be consistently delivered across the entire customer journey. Companies are re-engaging their potential customers with smarter product recommendations through showcasing ads with highly relevant products instead of posting generic social ads. Context-based personalization allows immediate benefits.

4. Predictive personalization will continue to prevail and AI is no longer just a hype
AI and machine learning are no longer merely buzzwords and trends. There will be lesser one-time or one-dimensional projects as the analytics models will be embedded behind the scenes to drive personalized engagement with customers and to fully transform an organization by positively impacting revenue. Brands will place a far greater emphasis on having more quality data as personalization efforts will become more highly detailed.

In 2020 and beyond, brands will continue to invest in predictive analytics and leverage a powerful platform to fuel personalization. Many brands are already using it, with Netflix and Spotify leading the way. Using previous consumer data and algorithms related to browsing patterns, predictive analytics plays a crucial role in optimizing marketing campaigns and helping brands determine customer responses.Building and releasing predictive models from many years of historical data can be an overwhelming project that might never see daylight. The key is to start small and release often.

5. Loyalty is shifting and directed now towards relevance
Personalization may be a future-proof way for brands to understand customers and retain them, but the digitization of everything and today’s advances in technology push brands to go even further. The best use cases of personalization show delivering customer engagement not just at the end of the shopping funnel, but throughout the customer journey. So even first-time website visitors will discover increasingly relevant experiences.

Loyalty still matters, but it will no longer be achieved only through rewards, discounts, and other offers. Technology has now evolved to let brands listen to the likes and dislikes of their customers and serve them accordingly. And with their demands and expectations swiftly rising all the time, digital marketers and ecommerce managers should customize and deliver a one-to-one digital interaction to reach their customers in a more relevant and engaging manner.

6. Push for hyper-personalized customer experiences
With the growth of online content and access to unlimited information, customers have more freedom to move between brands. They now have the power to let brands know what they truly want to win them over. They no longer wait for brands to tell them why their products are great, instead, they research and learn on their own.

With that said, great customer experience will no longer spell out only efficiency and convenience but will also demand extreme personalization. Improvements in technology have made it possible to learn more about their customers and make it easy to enable hyper-personalization from content to ads to design to product recommendations and everything in-between.

By aggregating the data into detailed and accurate segmentation such as device type, time, geo-location, and many more, the goal is to achieve a 1-to-1 message. This means that content – everything from brand offers and messages to product recommendations – can be served to specific customer types based on a specific context, giving marketing the power to affect customer behavior online on a whole new level.

7. More focus on omnichannel delivery
Features in movie streaming apps such as ‘continue watching’ and ‘watch from the beginning’ have revolutionized personalization. This approach is also being leveraged in ecommerce to enhance the experience of returning customers. For example, if a customer started their interaction with a brand on a mobile app, this experience would continue as the customer moves onto the website. By remembering the preferences of shoppers based on their previous sessions, brands allow customers to pick up exactly where they left off when they return.

In 2020, having a headless CMS in place to enable you to reuse the same content delivered through different channels will be more vital than ever before. It makes creating effective personalization easier. With smart TVs, mobiles, laptops, etc., customers are now more connected than ever, and they expect a consistent experience and high-quality content across all digital channels.

Omnichannel personalization allows brands to combine offline and online data to create customer profiles that deliver more tailored experiences across all customer touchpoints and more consistent relationships across all channels.

8. Technology consolidation into a single platform
The challenge of personalization becomes more complex because of the massive amount of data available on just one single person. Solving this requires moving a lot of the acquired information, collecting, tracking and data interpreting data. Marketing teams will now seek to find solutions that can integrate targeting requirements into a single yet comprehensive platform.

With the high volume of marketing technology acquisitions for the past years, along with new integrations across martech systems, a more consolidated solution with integrated capabilities will be more beneficial to marketers in the long run.For example, media company A-lehdet had more than a dozen websites with various technical solutions, but simplified it and came up with a technical solution flexible enough to meet the ever-changing demands and desires of its audience.

9. Creating trust to increase loyalty and drive growth
Trust will be an all-powerful commodity. So seeing personalization as a ‘quick fix’ for brands to solve conversion problems and improve revenues is a losing battle. As concerns about data use and general skepticism about how brands operate continue to grow, brands need to be extremely careful about how they use personalization. By doing this, an organization can demonstrate it is trustworthy and make consumers feel valued as individuals.

Delivering highly relevant messages is a golden ticket to creating long-lasting customer relationships, which ultimately drives loyalty and sales. But not at the risk of misusing data, which could not only spell disaster for an organization but also run the risk of irritating and losing customers.


Personalization will prove as a powerful investment and will gain a distinctive edge in the new decade. However, it will have to be accepted as a long-term strategy to increase brand loyalty and drive growth in the company. More and more brands will offer hyper-personalized recommendations and shopping experiences on multiple channels and at every customer touchpoint.

Ecommerce companies who take advantage of machine learning technology will see significant improvements in their personalization efforts. With all of the above tips and trends, the “Roaring ‘20s” nickname for the decade will surely hold true. Marketers will surely have their hands full as they strive to deliver on the promise of personalized customer experiences and aim for a narrowed gap between what customers expect and what marketers are able to deliver.

Ready to explore personalization? Start by completing our personalization maturity assessment and get your personalized report on where to start.  We’ve put this tool together based on our experience with implementing personalization across industries and clients over the last 10 years.

________________________________________________________________________________________

About the writer:

Mikael Gummerus

Mikael Gummerus is the founder and CEO of Frosmo. He’s a visionary and a firm believer in the adoption of microservices architecture, headless ecommerce, and CMS. With more than a decade of experience as a web entrepreneur, he’s passionate about growing consumer expectations of superior digital experiences.

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10 conversion rate optimization best practices in iGaming 2020

The iGaming industry is now a $45 billion business worldwide and is expected to grow at 14% annually. New regulations, technological advancements, and fierce competition are shaking up the way customers are betting online. Ever-growing numbers of iGaming operators are seeking to differentiate themselves to stand out from the crowded market by creating unique experiences.

The most important business objectives for iGaming operators are reducing unit costs in the acquisition, customer retention, and increasing customer lifetime. Many companies spend big on advertising to acquire new players but many of those efforts are diluted if the website isn’t performing to its best potential or meeting the players’ expectations for a good gaming experience.

In addition, advertising is becoming more regulated and is now restricted in certain markets, meaning that player engagement is even more important. One player experience doesn’t fit all, so it’s important to recognize the importance of tailoring player experiences to their individual preferences.

In this article, we’ve collected the best conversion rate optimization practices for your iGaming business in 2020 and beyond.

Costs of acquiring new players

 

 

A 10% improvement in conversion reduces the acquisition cost by $41 per player and improves the profit margin by 8%.

 

 

 

1. Tailor player experience to their individual needs

One size doesn't fit all in iGaming

Recognizing individual player needs is the start of better conversion rates. This is called personalization and it starts by knowing your players’ preferences and defining the segments the players belong to. What casino games are they more likely to play? What sports team do they follow? What is their favorite horse? How willing are they to try something new? Most commonly recognized player segments for iGaming are based on:

  • Marketing source
  • Interest identification
  • Player profile identification
  • New or returning players
  • Understanding player intent
  • Early churn potential
  • Early VIP potential

The best results in conversion rate optimization are generated when historical player data from different channels is combined with real-time behavioral data. This combination of data can be used to deliver personalized recommendations, content, and promotions that players are most likely to engage with. Engaged customers will lead to better customer retention rates and higher customer lifetime value.

 

2. Make the homepage relevant for your players

By now, we’ve established that for the iGaming business to thrive, the player experience needs to be exceptionally good and personalized, but player experience requires much more than a pretty website. Ultimately, it’s about understanding your players’ needs and personalizing the player experience while reminding them of the thrill of finding new games to play.

The aim of any personalization is to offer content or guidance that is relevant to a player’s situation and individual needs. The relevancy drives the likelihood of conversion rates and transaction value. When you know your players, personalization can be applied dynamically based on a horse race, or game schedules, the player’s channel (e.g. mobile, desktop), geolocation, time of day, or real-time behavior. For example, if a player is behaving in a way that can be interpreted as a high intent to convert and purchase, you might want to promote options such as live games or new bets.

Personalization will allow you to take advantage of that intent, leading to greater conversion rates and customer satisfaction. The ability to show relevant and personalized content on the first page of your service can have a 4x impact on conversion rates. For example, ushering your roulette-playing live casino customer back to your service and directly loading the live roulette game lobby. Or ensuring that a Real Madrid football fan who bets routinely on the team is served a pop-up acknowledging this type of behavior and welcomes the player with Real Madrid-themed content and a relevant bet option.

Here are examples of tailored personalized experiences that are tied to business objectives:

Tailored personalized experiences that are tight to business objectives

Customer case: When a user visits TwinSpires, they’re usually ready to bet on their favorite event or horse. So it makes sense to highlight that particular event or horse as early as possible in the player journey. By personalizing which races a user sees, and segmenting according to previous behavior on the site, the convenience of using the site greatly increases.

TwinSpires relies on Frosmo to increase conversions and acquisitions

 

3. Learn from player behavior with the help of AI

The preferences of players are difficult to predetermine and preferences also change over time. Artificial intelligence accelerates understanding player behavior which is the first step towards an excellent player experience. Here are some of the best practices on how to continuously learn about the players’ behaviors and how to implement those learnings to offer them the most suitable games, bets, and content. Collaborative filtering is a common technique to find similarities in players and recommend the next slots or games according to the most views and played games.

The main applications of collaborative filtering can be:

  • Discovering similar players.
  • Discovering similar games.
  • Finding the potential interest of a user in specific products for targeted marketing (recommendations).

Apply AI for VIP user prediction. Only between  1-  and 5% of players are VIP users but they contribute 60- to 80% of the revenue and are therefore a very important group to any iGaming operator. Earlier and more accurate VIP customer prediction models bring better customer lifetime value. For a player, AI creates a more immersive and fun gaming- and betting experience. With AI, you can create a feeling that the casino is tailored to the player’s individual needs. Plus,  AI helps identify behaviors that might lead to loyalty early on and is then able to serve those customers with special offers and player journeys.

For the best conversion results, real-time onsite behavioral data should be combined with the CRM data. Individual VIP player prediction can achieve an accuracy of up to 86% in as early as 3 days after sign-up. Prediction data is used to tailor the journey according to the players’ interests, including streamlined navigation bars, call-outs, recommended games based on profile and real-time behavior, reorganized game listings, and campaign targeting. More examples are given later in this article.

Reduce churn as early as possible. By definition, churn represents the act of a customer leaving the platform for good and specifically, in iGaming the churn rate is relatively high. Therefore, it is important to address customer churn early to employ a successful retention methodology. Implement supervised machine learning models to learn from users’ past behavior (CRM data) and predict future probabilities of  a user leaving the service.

 

4. Use social proof to promote games and drive a sense of urgency

Social proof plays a major role in your players’ purchase decisions. Even when people are impressed by your services, they almost always look at the actions of others to guide their decision-making process. Simply, social proof helps you build trust in your online business. You might want to show the first-time player how many active players there are on the site and what they are playing at that particular moment. Testimonials and game ratings are also effective social proof to promote games and increase conversions.

 

5. Cross-sell for better customer retention and customer lifetime value

Different platforms for casinos and sports bring challenges to iGaming operators as they typically don’t share customer data and insights. With personalization, the behavioral data can be easily shared between the two platforms allowing highly targeted content tailored to players’ preferences. This can also create opportunities to cross-sell between the platforms, such as displaying casino games that the player is most likely interested in and showing the content in the most relevant areas when the visitor is most likely to engage.

This approach provides a connection between your two main products, which will increase engagement and conversions. The best practice in providing the cross-sell promotions of casino games is to use collaborative filtering combined with player segmentation.

Customer case: Dafabet introduced new hovering menus to their site, where new and old games can be recommended to players in a more personalized and visual way. By suggesting new games according to the customers’ tastes, Dafabet has been able to increase their gross sales significantly.

Dafabet Connect receives 65.6% of their downloads through Frosmo modifications

6. Achieve player loyalty and retention with these proven tactics

Keeping the right customers is valuable because their conversion rates are naturally higher without high acquisition costs. According to Harvard Business School, a 5 % customer retention improvement can easily lead to a 25 to 95% increase in earnings. That’s why it’s important to pay attention to loyalty and retention tactics. Below are some examples of proven methods that are driving loyalty and retention.

  • Make returning customers feel welcome through dynamic front pages showing content according to the last played or the most played game.
  • Predict VIP players and those who are about to churn. Use social proof tactics and show promotions to engage target players.
  • Use RTP figures to recommend certain games to individual players to help them be successful.
  • Use gamification to increase player participation e.g. introduce progress bars and reward callouts during games.
  • Use personalized CTAs to push the right bonus at the right moment. Use deposit callouts and smart deposit preset to acknowledge the fact that players’ deposits are getting low.
  • Maximize the time that the players are in your service. Implement recommendations and show new games and casino slots according to the players’ interests.
  • Drive CTAs and recommendations as A/B tests or with AI-powered multi-armed bandit testing to show the most relevant games and content according to players’ behavior.
  • Elastic search bars learn and self-optimize to display relevant content according to a player’s personal intent.

 

7. Recommendations for better engagement

Recommendations are a powerful way to increase conversion rates and the player’s lifetime value. AI-powered recommendations ensure that you’re harnessing all of the data available on every touchpoint of your service. You can leverage this data to start predicting what slot/game/market your player would like to see next. This continuous combination of learning from a player’s product interest, their profiles, and the context of their visit, means that you can offer highly targeted, relevant, and engaging content.

Statistics in iGamingRecommendations could reorder your casino lobby by creating an entirely new look and feel, or vary which sports markets are displayed to each user. Doing this provides a relevant and engaging experience that will increase retention. Accenture has stated that 91% of consumers will remember a brand and be more likely to return when they have been provided with relevant offers and recommendations to engage with. We’ve seen brands experience a 20% increase in customers engaging and viewing casino content when their sports lobby has personalized recommendations.

Customer case: 188BET can be sure that they are serving the right content to the right customer at the right time while minimizing their churn rate. Machine learning helps them select content based on a deep understanding of the players’ preferences.

188BET collaborates with Frosmo to reduce churn and grow lifetime value through artificial intelligence

8. Experimentation and testing

Hypothesis-driven developmentTesting is always crucial as many improvements can cumulatively turn into big conversion rate generators. Testing helps you gather data to show what should be developed next, reduce costs risks, understand the audience on a deeper level, and solve visitors’ pain points. We recommend starting testing with a solid hypothesis – know why you want to test, your conversion rate goals, and your expectations. Use A/B/n testing to find out which variations perform better on a website. Examples of what you can test are banners, recommendations, navigation, CTA’s, social proofs, and content.

Learn more about A/B/n testing from this short video:

A/B/n testing

Multi-armed bandit testing makes testing faster and smarter with machine learning. With multi-armed bandit experiments, you can continuously learn and optimize your site while running your test. You’ll be earning while conversion rates are going up.

Learn more about multi-armed bandit in this short video:

multi-armed bandit

9. Empower affiliate connections

The customer journey starts with the affiliate website and the continuous player journey needs to be built from that point. Improve your conversion rates by focusing on dynamic content on the front page through personalized player journeys. Your affiliates will benefit too, as the value will be maximized against competitors and will responsibly increase customer lifetime value.

10. AI for fraud detection and responsible gambling

Fraud and abuse can incur a significant cost for iGaming operators. The ability to detect them and take early action can have a significant and positive impact on your bottom line. Machine learning helps identify and make real-time judgments when a player shows behavioral patterns that are consistent with bonus abuse, promotion predators, and account hijacking. These measures also shield honest players, providing smoother user experience.

Responsible gambling operators ensure that their customers know to stop when the fun stops.  The introduction of machine learning algorithms can be deployed easily and quickly to identify users who are likely to self-exclude. Other ways to utilize machine learning include methods such as reality-check messages, promoting the setting of the account limits, and offering a time-out. With advanced segmentation, a customized player journey can match individual needs and tastes, while remaining responsible.

 


About the writer:

Tanja Säde is the Chief of Marketing at Frosmo. With 20 years of experience in technology marketing, she is always curious about the latest technologies and marketing trends. She is enthusiastic about creating superior digital customer experiences through data, personalization, and AI. Outside of work, she is a yoga addict.

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The future of customer acquisition for media companies

During the past few years, I’ve sold Frosmo products and services to a whole range of companies. From our national lottery and casino, Veikkaus, to big international retailers like Clas Ohlson. However, as far as ecommerce is concerned, their digital challenges are all pretty similar. The major exception to that is the media industry.

And that’s because media companies face a unique problem; they have to charge money for something that people expect to be free. As a result, these companies have been relying on technical innovations even more than others in a bid to change the business model and stay relevant. It really has become adapt or die.

To be part of that reinvention of an industry by providing the software and solutions has been a great ride so far, but really one that’s only just getting started.

The points I’ll discuss in this article:

  1. Microtransactions
  2. Competing with social media
  3. Editorial content
  4. Natural Language Processing
  5. Targeting vs. testing

Intro to Frosmo and Media

Before I go into the trends that we’re helping media companies with right now, I think it’s good to look back at what we’ve done previously. And at this point, it’s also good to recognize the effort put in by our own developers and project managers to crack a market that was on a losing streak. It’s what has turned our experts into experts and Frosmo into a go-to place for the media.

Some of Finland’s top digital newspapers and streaming services have been improved with Frosmo. They’ve used the Platform to add and improve content recommendations, make layout changes, gamify reading experiences, optimize websites for mobile, add personalized paywalls, and much, much more.

The Frosmo Platform makes it fast and easy for front-end developers to change websites without having to access the back end. This concept enables endless development flexibility. Combine this with data, market trends, and the ideas of your digital team, and together with the Frosmo Platform, you can turn any website into a superior browsing experience, personalized for every occasion.  

 

Implementing future solutions for customer acquisition in media 

Implementing future solutions for customer acquisition in media

And that brings us to the solutions of the future. Web development is a continuous process and so is the quest for additional revenue and customer acquisition. An increasingly hot topic is microtransactions. You may know these from games and now online newspapers and magazines are looking to make use of them, too.

 

1. Microtransactions

For media, microtransactions means that Frosmo sets up a sort of mini paywall for readers to consume just a single article or get unlimited access for a week or two. The setup is a win-win for the consumer and for the newspaper, as the consumer doesn’t have to buy an entire subscription just to read something they’re particularly interested in and at the same time, the person gets used to spending money to consume news.

While it’s too soon to share any figures just yet, I think that microtransactions are here to stay and perhaps even become their own source of revenue.

Using the Frosmo platform, it’s pretty easy to create well-converting mini paywalls by taking into consideration the reader’s preferences. Once these preferences are established by tracking behavior and identifying the categories that the reader is most interested in, relevant articles can be gated off and the existing paywall can be used guide people to the right purchase funnel.

 

2. Bringing the conversation back to the website

Bringing the conversation back to the websiteAnother challenge that media companies are facing is that the conversation has shifted to social media. On one hand, it’s good for these companies that their content gets shared on social media, but it also leads to a decrease in sessions and number of articles read, which in return negatively impacts ad revenue. In general, people who click on an article on Facebook are still in the mindset of “browsing Facebook” rather than “reading the news”. As a result, they read one article and then go back to cat pictures.

In essence, you’re now competing with social media over someone’s time. And to win that battle, it’s important to offer more relevant and more engaging content. You really, really need to get your layout and recommendations right, as you only get one shot to grab the reader’s attention.

Frosmo has a few tricks up its sleeve to help with both the layout and recommendations, which is the next point of discussion and by using machine learning methods such as Natural Language Processing, further discussed at point 4.

 

3. Layout changes, especially editorial

Layout changes, especially editorialOne of the main reasons why people are loyal to certain news sites and magazines is because the tone and standpoints match theirs. Opinion pieces play a huge role in showing an outlet’s identity and they are great conversation starters. The same can be said for thorough investigative pieces. And in both cases, people love sharing them.

However, shorter-than-ever concentration spans rarely go well with long-form articles since there are tons of distractions on a website. Normally, clicks are great because you want users to read and explore, but a lot of resources have gone into these often important topics.

To really get people engrossed in the story, and to make people visually show that people are getting their money’s worth, the article has to look premium. This means blocking out distractions and finding novel ways to add visuals.

While changing page layouts and rearranging content is the majority of the work done with the Frosmo Platform, it’s still not that often used for these one-off occasions. And that’s a missed opportunity that I think will change the coming year as companies are more and more willing to invest in differentiating factors to add value and at the same time people are more willing to pay for quality.

 

4. Improving recommendations through Natural Language Processing

Improving recommendations through Natural Language ProcessingLike pretty much every self-respecting tech company these days, we’re investing heavily in machine learning. We’re all very excited about a model that we’re building that’s using Natural Language Processing or NLP in short.

NLP matches content to content with greater precision for example by analyzing the words in an article and assigning a similarity score. Displaying articles with higher similarity scores then leads to more accurate and higher converting recommendations. These recommendations can then be refined further by excluding already read articles. And better recommendations translate into more clicks and conversions.

One thing that we’re experimenting with is the way we can transparently show the machine learning outcomes. Showing the generated tags alongside each article in the Frosmo Platform would be one way to avoid black box problems. At the same time, we’re looking to make the outcomes manipulable so that anyone in the ecommerce team can make tweaks, rather than just data analysts or scientists.

And this is extremely important because understanding the data and outcomes within the ecommerce team is hugely beneficial for business development. It enables data-driven development and helps teams understand what should be changed or tested in order to reach the intended business goals.

This leads to another topic which I’ll cover in my next blog post: attribution modeling. My experience says that those companies which are doing well have C-level management that cares about the attribution modeling of your AI. The core of business development is to manage your customer journeys and this can go horribly wrong if business goals and usage of data are not talking to each other.

 

5. Separating targeting and testing

The last trend that I want to highlight is more of a workflow or methodology change than a technical or usability improvement. And that is the need to stop developing everything at once. Specifically, to separate targeting from testing, at least in the setup stage.

User journeys are so complex that even the slightest change can have an (adverse) effect on test results. As such, it’s important -perhaps vital?- to figure out your initial targeting criteria and make layout changes accordingly prior to running tests. Think of targeting as a long term effort and testing as an additional short term way to improve targeting results.

A great way to improve results for certain targeted audiences is multi-armed bandit (MAB) optimization, a form of “testing” where an algorithm decides which variation gets shown to whom. While it can be used to find winning variations in a short amount of time or on pages with less traffic, where it really shines is when you let MAB experiments run continuously.

For example, if you have a carousel with news recommendations, MAB could be used to rearrange the order of which article gets shown when based on conversions. Then, when a new article is published, it can automatically replace the worst performing content with this fresh piece. It guarantees the most amount of clicks, indefinitely.

 

Innovation never ends

Innovation never ends

 

Media companies have started figuring out what works, but that comes with its own risks. It seems that most media companies have now found themselves after the initial shock of the digitalization wave has worn off. But there are still many challenges and opportunities like the few seen above.

Staying fresh and relevant through continuous development and innovation is key to the consumers’ hearts. Never forget to innovate, the faster and easier the better. And fast and easy, isn’t this what we all are looking for, regardless of whether we’re developing or consuming?

Let’s chat about your media sites. You can find me on LinkedIn.

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About the writer:

Timo Vuori is a sales leader with eight solid years of experience in solution sales and business development in ecommerce and SaaS. He has created dozens of digital solutions for international clients in sectors including retail, travel, online services, banking, gaming, and telecommunications. Working in a groundbreaking industry with cutting edge technology, he keeps himself always up to date on the latest technologies and recent development in AI, voice search functionalities, and the evolution of internet buyer journeys.

Results-focused, Timo’s passion is to create lasting relationships with his customers and find a “win-win” in any situation. He believes that the route to achieving competitive advantage is through an understanding of global markets and industry trends and creating a winning alignment of business strategy and technology.

 

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4 most powerful phenomena in ecommerce marketing that every CMO should start adopting now

The first 3 phenomena personalized customer journeys, AI, and experimentation have been around for a while now. It’s good to see that after years of talking about them, we’re finally starting to see great results from brands that are embracing AI and personalization tools and using them as part of their core business models.  

An interesting new trend that marketers should start looking into is Progressive Web Applications (PWAs), as they bring many advantages to marketers who are looking for better reach and coherent omnichannel customer experience.

It all comes down to the fact that brands have now realized that putting the customer first and embracing their differences by creating personalized customer journeys is the only way to keep up with the competition and grow.

1. Personalized customer journeys

It’s very difficult to create superior customer journeys if you still think of segments as large groups based on demographics, location or some other loose definitions. Every buyer is different and you need to be able to delight every individual. Designing and implementing online customer journeys improves customer satisfaction, lowers customer acquisition costs, and makes customers loyal.

Janne Timmerbacka, ICT director of online grocery store Kauppahalli, sums it up nicely:” The best customer service isn’t based on profiling customer sets any longer. Every single customer is different with their needs and preferences. In an online grocery store, great customer experience is made from knowing the customer so well that you are able to delight the customer by recommending products of their interest”.

To get to that individual level of highly personalized customer journeys, real-time behavioral data of the visitors is needed. What they click, how deep they scroll, what they read, watch, and download will give you a lot of insights on how to direct them to find more relevant info for their individual needs.

2. AI

To go deeper with personalization, AI is needed.  Forbes just concluded a study that   AI-powered marketing campaigns increase customer engagement by 7x and revenue  3x by helping marketers become more targeted, more relevant in their content, and more effective in how they engage with each individual customer.

So with that in mind,  an AI-powered recommendation engine is definitely something that every ecommerce business should invest in this year. Think of it as a great way of serving your customers better, as they can find new interesting products or content to consume. In an article, Netflix said that its AI-powered personalized recommendations save them $1 billion in revenue annually by avoiding canceled subscriptions.

Kristina Lagerroos, Development Manager for the global leading brand in functional kids’ wear Reima, says, “Frosmo enables us to create winning user experiences by providing a recommendations engine that brings value to our customers. They help us to understand our customers’ preferences better and make data-driven decisions”.  

Natural Language Processing (NLP) is also a very interesting phenomenon in that regard. NLP is a subfield of AI that focuses on enabling computers to understand and process human languages or at least get a tiny bit closer to a human-level understanding of language. It ’s cutting edge and a great way to show your visitors more relevant content.

For example, it can be used as the basis for an algorithm that recognizes words in the site content and makes recommendations based on similarities. If a visitor reads an article about a specific topic, the algorithm recognizes the relevant keywords and crawls other articles to find the same keywords. These articles are then recommended to the visitor. This method offers great user experiences also for those first time visitors whom we wouldn’t otherwise be able to serve according to their interests.

3. Experimentation for data-driven decisions

At times, the most challenging part of running an ecommerce business is to get people to work together and agree to website changes. Thus, validating customer journeys through experimentation is the key to gather data and make more insightful data-driven decisions that everybody can agree on.

Multi-armed bandit (MAB) is a powerful AI-powered experimentation tool. With MAB, you test different variations on your website and direct traffic towards those variations that are performing the best. Small changes might turn out to be big revenue generators. That’s the reason why testing is essential and why testing with AI offers a powerful advantage.

Clas Ohlson uses multi-armed bandit to optimize the most promising product recommendations in different markets and in doing so, enabled them to increase their average order value by 8% and the product rows by 27%.

4. Progressive Web Applications

Progressive web applications (PWAs) are web applications that load like regular websites. It allows end users to have a mobile app like experience when visiting the main website, including a home screen and push notifications. From a marketing point of view, one of the biggest advantages is that customers get the same user experience as on the main website without being tied to any app store. These are the reasons we’ll see many ecommerce sites turning into PWAs during this year.

Let’s start creating superior digital experiences with personalized customer journeys!

Request a demo

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About the writer:

Tanja Säde is the Chief of Marketing at Frosmo. With 20 years of experience in technology marketing, she is always curious about the latest technologies and marketing trends. She is enthusiastic about creating superior digital customer experiences through data, personalization, and AI. Outside of work, she is a yoga addict.

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This year, Frosmo takes the digital experience to a new level

Frosmo future

Frosmo’s mission is to help your digital business become insight-driven. Our partnerships aim to grow your revenues with fewer resources. Technologies related to digital experience are taking huge leaps and Frosmo wants to ensure that you can get more out of your systems and processes. Our big themes for 2019 are:

Ease of use of the Frosmo Platform

We’ve created high-quality training courses to ensure that you get the best out of the Frosmo Platform. We’re also implementing tutorials and videos to improve the usability of the Frosmo Control Panel.

Headless & micro-services architecture

Experimentation and personalization shouldn’t be separated from your core systems. Frosmo wants to stand out from the market as the system-compliant digital experience solution. As the world is going headless, Frosmo can help you take advantage of the latest JavaScript frameworks and easily add personalization and other business management features to your modern front end. Read more about the headless approach.

Data integrations

After investing in data management platforms and CRMs, the challenge is how to turn the data and insights into actions. Frosmo continues to develop solutions to connect all major DMPs and CRMs, and other data sources easily and real-time to your front end.

AI

Frosmo continues to invest in AI. We have a new 1M€ development programme (we also invested 1M€ in 2017-2018) for AI solutions together with Business Finland. We have 3 levels of AI currently available for you and we continue to improve all of them. The first level is automated testing with the multi-armed bandit, the second level is AI-powered personalization and recommendations from any data source, and the third level is hybrid-modeling where we combine historical data into near real-time front-end behavior.

Personalized customer journeys

We want to help you to easily implement relevant and powerful personalized customer journeys for multiple different customer segments. They help grow revenues and retain customers. In addition to creating customer journeys with Frosmo, it’s very important to test, simulate, and easily try out all these different permutations. We’re working hard to make this process as easy and as profitable as possible.

Here’s to hoping 2019 will be big and successful for all of us. Looking forward to another great year!

Want to see Frosmo in action?

Request a demo

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About the writer:

Mikael Gummerus is the founder and CEO of Frosmo. He’s a visionary and a firm believer in the adoption of microservices architecture, headless ecommerce, and CMS. With more than a decade of experience as a web entrepreneur, he’s passionate about growing consumer expectations of superior digital experiences.

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