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How AI is Transforming Affiliate Marketing – ReadWrite



How AI is Transforming Affiliate Marketing - ReadWrite

The spending on marketing automation has been increasing steadily over the last few years. By 2023, the AI segment may hit the $25 million mark. AI will also reflect the spending strategy of about 55 percent of marketers. Also, it reflects the smaller picture of the AI market; it is all set to reach the threshold value of $190 billion by 2025.

Thus far, companies have benefited immensely from their investment in artificial intelligence (AI) and machine learning (ML). Whether AI is about the generation of leads or clicks or determining consumer behavior, the combination of the virtual entwined twins has proved to be useful.

Affiliate Marketing and AI

Affiliate marketing has also brought in several other benefits. Consequently, several changes are apparent on the surface of affiliate marketing. Read on to know about affiliate marketing in detail.

Ways in Which AI is Transforming Affiliate Marketing

In recent years, AI has changed the landscape of affiliate marketing in several ways. Here’s how it has helped affiliate marketing to evolve to its current form.

1. Affiliate programs based on real-time data

Together with machine learning algorithms, AI makes a positive contribution to the study of consumer behavior. Both work in tandem with one another to provide structured as well as unstructured data.

With the help of this information, vendors and affiliate publishers of a brand can quickly identify business prospects or target audiences and promote products among them. The information originating from AI is data-driven and inspired by the insights of big data. As a result, it helps affiliate marketers meet their objectives in a more pronounced way.

As is the case with most marketing campaigns, tracking plays an important role in affiliate marketing. Affiliate marketing tracking gives an insight into the effectiveness of a marketing program. The best way to track your performance on this front is to deploy affiliate marketing software such as Voluum dotcom.

2. Keyword-research-based content optimization

The presence of long-tail keywords is of paramount importance for the optimization of SEO-specific marketing strategies. The piece of content that originates from such keywords effectively engages the target audience. AI and machine-learning models play a crucial role in generating such keywords.

For particular affiliate niches, there is no substitute for less competitive and context-based keywords. The use of search keywords in affiliate marketing based on intent yields effective results in the form of the desired conversion of the leads.

AI models come in handy in A/B testing, with which the KPIs of two products in close competition with one another can be compared. Aside from drawing an accurate comparison, it also helps change UI/UX design plus contextual blogs and several other aspects.

These include video ads, e-books, banners, and landing pages. AI also helps bloggers create content that draws the attention of readers towards a specific product of a brand.

3. More leads and the conversions of those leads based on artificial intelligence (AI)

With AI models and APIs, autoresponders deliver exceptional results in terms of lead generation and conversions. From aut0-optimizing emails to reading the consumer behavior in real-time scenarios, the role of these components is well defined.

Another specialty of AI is its browser tools, coupled with algorithms, that help scan specific niches’ products. Besides, they can also identify bloggers, platforms, and forums linked with specific niches and target them. Apart from lead generation, these actions also help with lead conversion.

4. In-depth knowledge based on dashboards

Artificial intelligence (AI) can track the performance of advertisements from time to time. It also generates relevant KPIs for affiliate programs with the same level of efficiency and effectiveness.

On average, it plays its part in generating the following three kinds of KPIs:

  • Pay Per Scale
  • Pay Per Click
  • Pay Per Lead

AI models help predict similar KPIs by analyzing a huge chunk of data and yield higher conversion for affiliate marketers and the brands with which they are linked. This feature is one of the aspects that has made AI a must for affiliate marketing campaigns.

5. Higher level of engagement with business prospects

These days, most customers prefer to engage with the representatives of various brands n some way or the other for solutions to their issues. They may also do it to get an answer to their queries. Ever since the emergence of AI, the manner customer engagement has taken a 360-degree turn.

Chatbots have taken charge of the bulk of the interaction. In conjunction with affiliate programs, they help promote products alongside answering customers’ queries and resolving their issues.

Again, AI algorithms play an extended role in it. Among other things, algorithms based on AI models identify keywords in customers’ messages based on users’ intentions. Thereafter, chatbots provide customers with affiliate marketing links based on their consumer behavior.

Final thoughts

To sum up, these are some of the ways in which AI has guided the affiliate marketing sector to its current form. AI is an evolving domain; however, only a part of it has been explored. Experts believe its scope will extend along with its advancement in the future. Depending on this aspect, it may help transform affiliate marketing in additional ways.

Image Credit: provided by the author; thank you!

Jasika Adams

Jasika Adams is a writer with a passion for writing on emerging technologies in the areas of human resources, startups and business management. She is a talent acquisition manager currently associated with Index Time Clock. In her free time, she loves to play with her kids and read mystery books.


Fintech Kennek raises $12.5M seed round to digitize lending



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 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.

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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



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



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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