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The Role of AI and ML in Improving Digital Performance – ReadWrite

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Curate and Create Better Content


Artificial intelligence and machine learning are among the top marketing buzzwords we come across in the field of digital marketing. These technologies have already become an integral part of digital marketing and are being leveraged to make campaigns more personable and efficient.

For instance, artificial intelligence can make personalization easy and quick by creating accurate buyer personas. These personas are auto-generated to deliver a holistic audience segmentation, thereby improving the effectiveness of the campaigns. In addition, Netflix, Google, Uber, Spotify, Pinterest, and other apps use machine learning to personalize individual accounts and make relevant recommendations to their users.

The ever-improving algorithms and the exponential growth of data are encouraging business leaders and marketers to use AI, in the form of machine learning, natural language processing (NLP), deep learning, and other technologies. These technologies are helping them improve customer experience and conversions.

A Gartner survey shows that 37% of organizations are applying AI in some form or the other to boost their digital performance.

This post highlights how AI and ML are proving to be game-changers in the digital marketing realm.

1. Offer a Better Understanding of the Audience

Great content starts with knowing the audience well. When a business knows its target audience, the connection feels more natural and relevant. That genuine connection goes a long way in building lasting relationships with customers.

In recent years, AI and ML have opened up a whole new world of possibilities for understanding audience behavior. AI tools and data-driven insights are helping businesses understand who they are reaching, what the customers want and need, when to communicate, and where to reach them.

Artificial intelligence helps marketers instantly define buyer personas. Then, platforms like Socialbakers auto-generate these personas to deliver more holistic audience segmentation in the form of actionable insights. These insights help content marketers share inspiring stories that convert.

Keeping your audience at the center of your online strategies is critical to business success. AI can help by offering unique audience insights, enabling businesses to deliver an integrated brand experience through relevant content. It also helps in selecting the most trustworthy and effective influencers for the brand.

2. Help with Lead Management

Big data, predictive analytics, and machine learning are being increasingly used in business intelligence these days. Machine learning, with its ability to bring out valuable hidden insights from large data sets, can create tangible value for businesses.

Leads are the driving force for businesses. They are the ones who will soon contribute to the organizational revenue. Hence, business leaders spend a significant amount of time in lead management. ML can be leveraged to improve and scale a firm’s approach to lead management, thereby boosting the bottom line. It helps firms generate better leads, qualify and nurture them, and ultimately monetize them effectively.

For instance, ML can help you create an ideal customer profile (ICP) to reach the best customers. ICP takes a structured look at the demographics and psychographics of an individual and determines their purchase intent and the content that matters to them. Thus, ICP can be used for lead scoring, allowing marketers to prioritize targeted accounts.

ML can also help firms generate more qualified leads from the traffic already coming to the site. For example, check out how Drift, a revenue acceleration platform, uses conversational AI to recognize quality from noise, learn from the conversations, and automatically qualify or disqualify website visitors. These qualifiers help the sales team focus on leads that are ready for conversions.

3. Curate and Create Better Content

AI is changing the game for content marketers. The technology is being used to automatically generate content for simple stories like sports news or stock market updates. AI also allows social channels to customize user new feeds.

But one content field where AI is increasingly applied is content curation. AI algorithms make it easier to collect target audience data to create relevant content at each stage of the marketing funnel.

For instance, the algorithms collect data on what the audience prefers to read, the questions they want answers to, or any specific concerns. Using this data, content marketers can curate and create relevant content that boosts customer experience and ultimately leads to conversions.

The North Face uses an AI-powered technology like IBM Watson that recreates shopping experiences. The AI tool uses cognitive computing that brings the online and in-store experiences closer together.

Besides, machine learning feeds content strategies by discovering fresh research-based content ideas, identifying the top-performing topic clusters, showing the most relevant keywords in a specific niche.

For instance, Google Analytics and SEMrush operate on machine-learning algorithms that are useful in keyword research and discovery, and content distribution. In addition, these tools can discover industry trends and show you ways to rank higher in SERP.

AI and ML-enabled tools improve the overall reception and performance of online content. In addition, the tools allow marketers to offer relevant and personalized digital experiences that positively influence engagement.

4. Help with Competitive Search Engine Ranking

Search engines are already using AI-enabled algorithms to deliver the most relevant SERP results. These algorithms rely on AI to understand the context of the content and spot irrelevant keywords. No wonder SEOs are constantly striving to understand these algorithms and coming up with strategies to create contextual, conceptual, and accurate content.

The placement of your business in the SERPs can make or break your online reputation and performance. AI technologies make it easier to create compelling content that answers the target audience’s queries, keywords, and phrases.

SEO isn’t a day’s job. It’s challenging, and the results of one’s efforts can only be seen after months. Fortunately, AI-based SEO tools help alleviate this stress. SEO optimization tools like Moz, WooRank, BrightEdge, and MarketMuse heavily rely on AI to offer SEO solutions like:

  • Keyword research
  • Search terms to make the content more relevant
  • Link-building opportunities
  • Trending topics
  • Optimum content length
  • User intent and more.

Tools like Alli AI can instantly optimize your website regardless of the CMS and your web development expertise. The platform performs a site-wide content and SEO audit, automatically optimizes the content, and resolves duplicate content issues. All this makes it easier for content creators to avoid poor-performing content and boost their online ranking.

5. Improve Page Speed

Google has put an exact value on fast user experience by including page speed as one of its ranking signals. That’s why boosting page speed is one of the top priorities for all businesses, especially ecommerce firms. As a result, Webmasters take all sorts of measures to improve page speed.

For instance, WordPress site owners may speed up WordPress by optimizing background processes, keeping the WP site updated, using a content delivery network (CDN), or using faster plugins. Of course, they also use various tools like Page Speed Insights, load time testers, and CMS plugins for the purpose. But now, there’s another ML-powered solution available for boosting the page speed – the Page Forecasting Model.

This model predicts user behavior using machine learning and predicts the next page visitors will click on in real-time. This allows Webmasters to preload the page in the background, thus improving the overall experience.

The algorithm is trained with historical data from Google Analytics.

For instance, user patterns like going from home page to category page or product page to the shopping cart are recognized, understood, and included in update algorithms. If the user behaves similarly, the algorithm is automatically prepared with the next page.

However, the prediction accuracy is dependent on the amount of data available to train the algorithm and the website structure. So, the models will vary according to these factors. For instance, if yours is an ecommerce website that combines industry news with product pages, it’s better to use two or more models that can predict the behavior per section.

6. Automate Website Analytics Process

Web analytics isn’t new. Businesses have been assessing user behavior and tracking key performance metrics since the mid-’90s. But thanks to AI and machine learning, web analytics tools now have robust capabilities that allow businesses to automate the process. These tools can offer auto-generated reports and on-demand insights that feed marketing strategies.

Within a single visit to a webpage, each user generates hundreds of data points like the time spent on a page, the browser details, its location, and others. It is practically impossible to analyze all this data manually. AI and ML make such analysis faster and accurate by speeding up the data processing.

AI-based tools can help you track each visitor’s online behavior, understand user journeys, and how customers move through the marketing funnel. They also point out issues, if any.

Let’s say you have a blog post that gets a lot of traffic, but visitors just read the post and leave without taking action like subscribing to your newsletter or sharing your post on social media. AI-based tools can flag such issues, allowing you to take the necessary corrective action like adding internal links or improving your CTA.

Google Analytics (insights section), Adobe Analytics, and Kissmetrics are among the top web analytics tools that help firms see patterns in customer behavior and predict future trends.

7. Improve Site Navigation

Site navigation is another critical area in digital performance where AI and ML can help is site navigation. Though it may sound negligible, the importance of having organized and easy-to-follow navigation cannot be ignored. Well-planned navigation improves the visit duration, reduces the bounce rate, and boosts user experience. It also enhances the overall aesthetic appeal of the website design.

AI can help Webmasters create a user-friendly website structure that’s easy to navigate. AI-powered chatbots can guide users through the pages and help them find what they are looking for within the first few clicks. This significantly improves the user experience and sends good signals to search engines, indicating that your content is useful and relevant.

Thus, Google and other search engines will rank your page higher than any other website offering similar content.

8. Design Better Websites

AI applications can improve the usability and experience of a website by enhancing the site’s appearance, strengthening its search abilities, managing inventory better, and improving interaction with website visitors. No wonder a growing number of designers and developers are moving towards AI-based design practices.

AI is slowly becoming an indispensable part of modern web design and development. Take the field of artificial design intelligence (ADI) systems, for instance. ADI has triggered a sudden shift in the way web designing is done. It allows designers to combine applications into the website for better user experience and functionality.

Check out The Grid website platform that automatically adapts its design to highlight the content. The platform uses ML and constraint-based design and flow-based programming to dynamically adapt the website design to the content.

Today, we have several entrants in this space that are taking AI in web design to a whole new level. Brands like Adobe, Firedrop, Bookmark, Wix, Tailor Brands, and many others are leading the segment and leveraging the capabilities of AI in web design. In addition, most of these ADI platforms can learn and offer suggestions for optimizing the website for better user experience and SEO performance.

The Way Forward

Artificial intelligence and machine learning are proving to be awesome technologies when it comes to improving a firm’s digital performance. However, it is essential to remember that these ML models are only as good as the data that’s used to train them. Therefore, it’s critical to ensure that your marketing team has access to high-quality and accurate data.

So, before applying these technologies to your digital efforts, there are specific steps that you need to take.

  • Set up tags to track and capture on-site user behavior.
  • House all the data from different sources in one central place like Google BigQuery, a Big Data analytics platform.
  • Invest in data deduplication to eliminate duplicate copies of repeating data from multiple sources.

Once your data is in place, you will be in a great position to start deploying AI and ML for boosting your digital performance. In addition, the information shared above will prove to be useful as you start building machine learning solutions for improving your business’s online presence.

Lucy Manole

Lucy is a creative content writer and strategist at Marketing Digest. She specializes in writing about digital marketing, technology, entrepreneurship, and education. When she is not writing or editing, she spends time reading books, cooking and traveling.

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Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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