MARKETING

Leveraging AI and Machine Learning for Personalization and Engagement

Published

12 months ago

May 6, 2023

Leveraging AI and Machine Learning for Personalization and Engagement

Thanks to today’s technology, businesses have access to various sophisticated AI and machine learning solutions that can help them enhance the customer experience through more nuanced personalization.

The following guide will introduce you to some of these solutions and show you how they deliver personalization at scale. It will also address the ethical challenges of using AI and machine learning and how to address them.

AI and Machine Learning’s Role In Personalization

Traditionally, products and promotional campaigns were tailored to appeal to a specific audience or group. Thus, marketing materials were typically static and unchanging, which made them inefficient.

Your business can’t thrive if it doesn’t know who its customer is. Thorough market research is essential to catering to each customer’s needs and building your customer experience around them. But creating individual custom experiences for consumers can be tricky. Not only does it require the amassment of large sets of data, but this data must be applied in meaningful ways.

This is the role of AI and machine learning in personalization and AI in personalization. They are data-centric tools that work by sifting through large sets of acquired data, sorting it and presenting it back to you based on an input, instruction (prompt), or configuration.

6 Examples of Successful Machine Learning and AI-driven Personalization

When the internet was still in its infancy, there was no personalization; everyone was exposed to the same information.

Then designers introduced templates with blank spots that could be filled with a site visitor’s details, such as their name or location. Soon marketers used strategies such as loyalty cards and programs to gather information about their customers. This information could then be used for personalization.

But we’ve come a long way since then. Here are a few examples of how AI and machine learning have been used to deliver more optimal personalization.

Targeted Advertising

Targeted advertising is likely the most popular application of AI and machine learning in marketing. Companies like Google and Meta use customer search history and usage behaviors to deliver personalized ads.

They also deploy AI-powered ad trackers that can determine how well an ad is performing, allowing them to adjust and improve their strategies.

Dynamic Web Design

An AI can learn about site visitors’ or clients’ preferences by observing their usage habits and behavior. This includes tracking their time spent on certain pages, products they frequently search for, etc. It can then dynamically shift the visual elements of your website, including fonts, colors, and themes.

Your website’s look and feel aren’t the only aspects of your website that machine learning and AI can improve. They can also gather information about suboptimal processes and web elements that may impede your website’s performance and ruin the customer experience. They can also determine which sections or parts of your website visitors spend the least time on or bounce away from quickly.

Enhancing Accessibility

Marketers and designers have become more attentive to the accessibility of their marketing campaigns and promotional materials. Not only does accessible marketing open you up to new customer bases, but it also has the potential to improve your brand’s reputation.

Content Recommendations

Your product and its delivery can be influenced by AI and machine learning. Streaming services are the most evident examples of this.

Machine learning algorithms are used to gather information about what users like to watch or listen to. They can then make listening or watch recommendations. They use the information gathered from other users as well to make these predictions.

Machine learning and AI also track actual viewing and listening habits. For instance, it will track if users prefer to listen to entire uninterrupted albums or mix-and-match playlists. They can also analyze how clients watch videos. For instance, do they prefer to watch movies in daily intervals or single sittings?

Personalized Customer Relations

Customer Relationship Management (CRM) software is where business intelligence meets customer experience. And, of course, CRM software has not been spared by AI-driven modernization.

Artificial intelligence can be harnessed to gather and process data from both internal and external sources. Predictive analytics offered by this system can provide organizations with unrivaled levels of customer intelligence.

Thanks to ChatGPT, more software companies have begun integrating generative AI into their software. Microsoft Co-Pilot and Salesforce’s Einstein GPT are two of the most famous examples. Generative AI can be used to relay faster responses to customers and determine the best ways to communicate with them.

This isn’t the only example of how AI is used in CRM software. Zendesk is one of the well-known software-as-a-service (SaaS) CRM software solutions. They use AI and cloud computing to deliver AI at scale. Whether through conversational AI and customer analytics, they’ve used this technology to revamp and revitalize their products by adding more personalization.

However, they’re not the only ones. There are a litany of Zendesk alternatives using AI to deliver truly innovative products, from AI translating messages and transcribing audio in real-time to AI sending custom message responses.

Artificial intelligence and machine learning have elevated nearly every business area and will continue to do so in the foreseeable future.

Computer Vision and Facial Recognition

Organizations can use tools such as facial recognition and computer vision systems to learn things about customers. For instance, if given permission, a machine learning algorithm could cluster all the photographed images on a customer’s phone to form a profile. These tools could potentially conclude that a customer enjoys certain hobbies or likes to eat out at certain restaurants frequently.

The Potential Ethical Challenges of AI and Machine Learning

Personal data and privacy were always concerns even before the advent and popularization of modern AI. Companies originally used strategies such as loyalty cards to extract data from customers and to understand their spending habits.

These companies would then use this data to offer customers personalized products and deals. Then smartphones became widespread, allowing companies to use metrics such as location (geolocation) and other data to deliver personalized ads.

All these forms of data gathering were introduced before current AI. Many of them can be considered unethical. So if these problems have always existed, how does AI make a difference?

Unethical Data Acquisition

AI can enhance the data acquisition process through monitoring and other techniques. It can ultimately amass and sort this data faster than a human operator, which, of course, may raise questions of privacy.

Bias

Unfortunately, machines and algorithms aren’t free from bias. After all, they’re made by human beings, and we’re naturally biased. As such, it’s only natural that algorithms built and trained by us would be as flawed.

An ML/AI model trained using data from a specific group is likelier to give unreliable predictions for people outside that group.

Employment

Marketing is cited as one of the many industries that will be impacted by AI, causing many of those working within it some concern for their job security. AI can post on social media, interact with clients, target potential customers, etc. It can perform these tasks more efficiently than human operators.

4 Potential Solutions for Ethical Implementation of AI and Machine Learning

Data privacy and the rules and regulations that govern them continue to evolve. The best way for companies to protect themselves completely is by not capturing personal data.

However, this isn’t technically possible, especially if you want to implement AI-driven personalization to drum up engagement. The next best step is to get informed consent or gather data in such a way that the user is always aware of it.

Giving Visitors Options

Not everybody’s comfortable with the idea of an Orwellian-like software program lurking behind the scenes, watching every move they make. Visitors must be made aware of your AI and machine learning software upon visiting your website. You can do it similarly to how most modern websites notify visitors of cookies and other privacy policies.

However, many websites do not always provide users with a way to opt-in or out of certain rules or settings. By using the website, you agree to all policies, including being monitored. Users can only opt out by choosing not to engage or use your website. Of course, this isn’t ideal as you want to direct more people to your website and keep your conversion rates healthy.

Instead, you can inform users of your policies and allow them to choose which portions they can opt in or out of. This will also allow you to acquire fully informed consent.

Even if they decide they’d rather disable your monitoring tools, other more ethical ways exist to extract information about them. In these instances, AI and machine learning may not play a part in the data acquisition process. However, it can still be used to apply personalizations dynamically.

Using Surveys and Quizzes

If you can’t use AI to gather data about visitors because they’ve found a way to block it or have opted out, there are still other creative ways to do this.

For instance, you can use surveys and quizzes to learn more about your potential customers. Now defunct UK-based fashion company Thread was a great example of how this strategy could be implemented well.

Their AI would send their clients weekly style recommendations based on information acquired from these quizzes. Clients would rate the recommendations, and Thread’s AI could then use these ratings to improve their suggestions. It’s no surprise that Mark and Spencer purchased Thread’s technology to enhance their own personalization capabilities.

Staying Up to Date With Rules and Regulations

As we previously mentioned, companies must adhere to many rules, standards and regulations when working with data. Some of the most well-known and significant include the EU’s General Data Protection Regulation (GDPR) and The American Data Privacy and Protection Act (ADPPA).

Non-compliance and infringement of the rules set out by these regulations can result in heavy fines or imprisonment. Thus, organizations must be cognisant of the data protection laws and regulations of their regions.

This can be tricky as both the technology and the rules that govern it continue to change. Fortunately, AI can help with this and ensure that your organization is updated on the latest news and regulation changes.

Moreover, it can automatically update your security and policies based on these changes. Ultimately, machine learning and AI can be used to tackle some of the ethical challenges they present.

Upskilling Employees

Businesses must remember not to dehumanize their employees. They must be proactive to ensure that they invest in the morale of their human staff, which includes coaching and upskilling them.

Companies should also consider hiring in-house counselors to help calm and quell the fears and anxiety of their employees.

Conclusion

As advancements in AI continue to accelerate, we’ll begin to see more discourse concerning the ethics of its usage. Many of the questions surrounding the ethics of using AI and machine learning tend to be philosophical. However, there are ways to approach these matters pragmatically.

Organizations must ensure guards are in place to protect customers’ privacy when using machine learning models and AI to extrapolate personalization data. Customers need to know what information is being recorded and what it’s used for.

AI and machine learning are great tools but should not be leveraged with near-reckless abandon. We can expect to see more literature and laws regulating their use in the future.

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MARKETING

Tinuiti Marketing Analytics Recognized by Forrester

Published

21 hours ago

April 19, 2024

Entireweb News Bot

Tinuiti Marketing Analytics Recognized by Forrester

News

By Tinuiti Team

Apr 16 2024

Rapid Media Mix Modeling and Proprietary Tech Transform Brand Performance

Tinuiti, the largest independent full-funnel performance marketing agency, has been included in a recent Forrester Research report titled, “The Marketing Analytics Landscape, Q2 2024.” This report comprehensively overviews marketing analytics markets, use cases, and capabilities. B2C marketing leaders can use this research by Principal Analyst Tina Moffett to understand the intersection of marketing analytics capabilities and use cases to determine the vendor or service provider best positioned for their analytics and insights needs. Moffett describes the top marketing analytics markets as advertising agencies, marketing dashboards and business intelligence tools, marketing measurement and optimization platforms and service providers, and media analytics tools.

As an advertising agency, we believe Tinuiti is uniquely positioned to manage advertising campaigns for brands including buying, targeting, and measurement. Our proprietary measurement technology, Bliss Point by Tinuiti, allows us to measure the optimal level of investment to maximize impact and efficiency. According to the Forrester report, “only 30% of B2C marketing decision-makers say their organization uses marketing or media mix modeling (MMM),” so having a partner that knows, embraces, and utilizes MMM is important. As Tina astutely explains, data-driven agencies have amplified their marketing analytics competencies with data science expertise; and proprietary tools; and tailored their marketing analytics techniques based on industry, business, and data challenges.

Our Rapid Media Mix Modeling sets a new standard in the market with its exceptional speed, precision, and transparency. Our patented tech includes Rapid Media Mix Modeling, Always-on Incrementality, Brand Equity, Creative Insights, and Forecasting – it will get you to your Marketing Bliss Point in each channel, across your entire media mix, and your overall brand performance.

As a marketing leader you may ask yourself:

How much of our marketing budget should we allocate to driving store traffic versus e-commerce traffic?
How should we allocate our budget by channel to generate the most traffic and revenue possible?
How many customers did we acquire in a specific region with our media spend?
What is the impact of seasonality on our media mix?
How should we adjust our budget accordingly?
What is the optimal marketing channel mix to maximize brand awareness?

These are just a few of the questions that Bliss Point by Tinuiti can help you answer.

Learn more about our customer-obsessed, product-enabled, and fully integrated approach and how we’ve helped fuel full-funnel outcomes for the world’s most digital-forward brands like Poppi & Toms.

The Landscape report is available online to Forrester customers or for purchase here.

MARKETING

Ecommerce evolution: Blurring the lines between B2B and B2C

Published

2 days ago

April 18, 2024

Entireweb News Bot

Ecommerce evolution: Blurring the lines between B2B and B2C

Understanding convergence

B2B and B2C ecommerce are two distinct models of online selling. B2B ecommerce is between businesses, such as wholesalers, distributors, and manufacturers. B2C ecommerce refers to transactions between businesses like retailers and consumer brands, directly to individual shoppers.

However, in recent years, the boundaries between these two models have started to fade. This is known as the convergence between B2B and B2C ecommerce and how they are becoming more similar and integrated.

Source: White Paper: The evolution of the B2B Consumer Buyer (ClientPoint, Jan 2024)

What’s driving this change?

Ever increasing customer expectations

Customers today expect the same level of convenience, speed, and personalization in their B2B transactions as they do in their B2C interactions. B2B buyers are increasingly influenced by their B2C experiences. They want research, compare, and purchase products online, seamlessly transitioning between devices and channels. They also prefer to research and purchase online, using multiple devices and channels.

Forrester, 68% of buyers prefer to research on their own, online . Customers today expect the same level of convenience, speed, and personalization in their B2B transactions as they do in their B2C interactions. B2B buyers are increasingly influenced by their B2C experiences. They want research, compare, and purchase products online, seamlessly transitioning between devices and channels. They also prefer to research and purchase online, using multiple devices and channels

Technology and omnichannel strategies

Technology enables B2B and B2C ecommerce platforms to offer more features and functionalities, such as mobile optimization, chatbots, AI, and augmented reality. Omnichannel strategies allow B2B and B2C ecommerce businesses to provide a seamless and consistent customer experience across different touchpoints, such as websites, social media, email, and physical stores.

However, with every great leap forward comes its own set of challenges. The convergence of B2B and B2C markets means increased competition. Businesses now not only have to compete with their traditional rivals, but also with new entrants and disruptors from different sectors. For example, Amazon Business, a B2B ecommerce platform, has become a major threat to many B2B ecommerce businesses, as it offers a wide range of products, low prices, and fast delivery

“Amazon Business has proven that B2B ecommerce can leverage popular B2C-like functionality” argues Joe Albrecht, CEO / Managing Partner, Xngage. . With features like Subscribe-and-Save (auto-replenishment), one-click buying, and curated assortments by job role or work location, they make it easy for B2B buyers to go to their website and never leave. Plus, with exceptional customer service and promotional incentives like Amazon Business Prime Days, they have created a reinforcing loyalty loop.

And yet, according to Barron’s, Amazon Business is only expected to capture 1.5% of the $5.7 Trillion addressable business market by 2025. If other B2B companies can truly become digital-first organizations, they can compete and win in this fragmented space, too.”

If other B2B companies can truly become digital-first organizations, they can also compete and win in this fragmented space

Joe Albrecht
CEO/Managing Partner, XNGAGE

Increasing complexity

Another challenge is the increased complexity and cost of managing a converging ecommerce business. Businesses have to deal with different customer segments, requirements, and expectations, which may require different strategies, processes, and systems. For instance, B2B ecommerce businesses may have to handle more complex transactions, such as bulk orders, contract negotiations, and invoicing, while B2C ecommerce businesses may have to handle more customer service, returns, and loyalty programs. Moreover, B2B and B2C ecommerce businesses must invest in technology and infrastructure to support their convergence efforts, which may increase their operational and maintenance costs.

How to win

Here are a few ways companies can get ahead of the game:

Adopt B2C-like features in B2B platforms

User-friendly design, easy navigation, product reviews, personalization, recommendations, and ratings can help B2B ecommerce businesses to attract and retain more customers, as well as to increase their conversion and retention rates.

According to McKinsey, ecommerce businesses that offer B2C-like features like personalization can increase their revenues by 15% and reduce their costs by 20%. You can do this through personalization of your website with tools like Product Recommendations that help suggest related products to increase sales.

Focus on personalization and customer experience

B2B and B2C ecommerce businesses need to understand their customers’ needs, preferences, and behaviors, and tailor their offerings and interactions accordingly. Personalization and customer experience can help B2B and B2C ecommerce businesses to increase customer satisfaction, loyalty, and advocacy, as well as to improve their brand reputation and competitive advantage. According to a Salesforce report, 88% of customers say that the experience a company provides is as important as its products or services.

Market based on customer insights

Data and analytics can help B2B and B2C ecommerce businesses to gain insights into their customers, markets, competitors, and performance, and to optimize their strategies and operations accordingly. Data and analytics can also help B2B and B2C ecommerce businesses to identify new opportunities, trends, and innovations, and to anticipate and respond to customer needs and expectations. According to McKinsey, data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain customers, and 19 times more likely to be profitable.

What’s next?

The convergence of B2B and B2C ecommerce is not a temporary phenomenon, but a long-term trend that will continue to shape the future of ecommerce. According to Statista, the global B2B ecommerce market is expected to reach $20.9 trillion by 2027, surpassing the B2C ecommerce market, which is expected to reach $10.5 trillion by 2027. Moreover, the report predicts that the convergence of B2B and B2C ecommerce will create new business models, such as B2B2C, B2A (business to anyone), and C2B (consumer to business).

Therefore, B2B and B2C ecommerce businesses need to prepare for the converging ecommerce landscape and take advantage of the opportunities and challenges it presents. Here are some recommendations for B2B and B2C ecommerce businesses to navigate the converging landscape:

Conduct a thorough analysis of your customers, competitors, and market, and identify the gaps and opportunities for convergence.
Develop a clear vision and strategy for convergence, and align your goals, objectives, and metrics with it.
Invest in technology and infrastructure that can support your convergence efforts, such as cloud, mobile, AI, and omnichannel platforms.
Implement B2C-like features in your B2B platforms, and vice versa, to enhance your customer experience and satisfaction.
Personalize your offerings and interactions with your customers, and provide them with relevant and valuable content and solutions.
Leverage data and analytics to optimize your performance and decision making, and to innovate and differentiate your business.
Collaborate and partner with other B2B and B2C ecommerce businesses, as well as with other stakeholders, such as suppliers, distributors, and customers, to create value and synergy.
Monitor and evaluate your convergence efforts, and adapt and improve them as needed.

By following these recommendations, B2B and B2C ecommerce businesses can bridge the gap between their models and create a more integrated and seamless ecommerce experience for their customers and themselves.

MARKETING

Streamlining Processes for Increased Efficiency and Results

Published

3 days ago

April 18, 2024

Entireweb News Bot

Streamlining Processes for Increased Efficiency and Results

How can businesses succeed nowadays when technology rules? With competition getting tougher and customers changing their preferences often, it’s a challenge. But using marketing automation can help make things easier and get better results. And in the future, it’s going to be even more important for all kinds of businesses.

So, let’s discuss how businesses can leverage marketing automation to stay ahead and thrive.

Benefits of automation marketing automation to boost your efforts

First, let’s explore the benefits of marketing automation to supercharge your efforts:

Marketing automation simplifies repetitive tasks, saving time and effort.

With automated workflows, processes become more efficient, leading to better productivity. For instance, automation not only streamlines tasks like email campaigns but also optimizes website speed, ensuring a seamless user experience. A faster website not only enhances customer satisfaction but also positively impacts search engine rankings, driving more organic traffic and ultimately boosting conversions.

Automation allows for precise targeting, reaching the right audience with personalized messages.

With automated workflows, processes become more efficient, leading to better productivity. A great example of automated workflow is Pipedrive & WhatsApp Integration in which an automated welcome message pops up on their WhatsApp

within seconds once a potential customer expresses interest in your business.

Increases ROI

By optimizing campaigns and reducing manual labor, automation can significantly improve return on investment.

Leveraging automation enables businesses to scale their marketing efforts effectively, driving growth and success. Additionally, incorporating lead scoring into automated marketing processes can streamline the identification of high-potential prospects, further optimizing resource allocation and maximizing conversion rates.

Harnessing the power of marketing automation can revolutionize your marketing strategy, leading to increased efficiency, higher returns, and sustainable growth in today’s competitive market. So, why wait? Start automating your marketing efforts today and propel your business to new heights, moreover if you have just learned ways on how to create an online business

How marketing automation can simplify operations and increase efficiency

Understanding the Change

Marketing automation has evolved significantly over time, from basic email marketing campaigns to sophisticated platforms that can manage entire marketing strategies. This progress has been fueled by advances in technology, particularly artificial intelligence (AI) and machine learning, making automation smarter and more adaptable.

One of the main reasons for this shift is the vast amount of data available to marketers today. From understanding customer demographics to analyzing behavior, the sheer volume of data is staggering. Marketing automation platforms use this data to create highly personalized and targeted campaigns, allowing businesses to connect with their audience on a deeper level.

The Emergence of AI-Powered Automation

In the future, AI-powered automation will play an even bigger role in marketing strategies. AI algorithms can analyze huge amounts of data in real-time, helping marketers identify trends, predict consumer behavior, and optimize campaigns as they go. This agility and responsiveness are crucial in today’s fast-moving digital world, where opportunities come and go in the blink of an eye. For example, we’re witnessing the rise of AI-based tools from AI website builders, to AI logo generators and even more, showing that we’re competing with time and efficiency.

Combining AI-powered automation with WordPress management services streamlines marketing efforts, enabling quick adaptation to changing trends and efficient management of online presence.

Moreover, AI can take care of routine tasks like content creation, scheduling, and testing, giving marketers more time to focus on strategic activities. By automating these repetitive tasks, businesses can work more efficiently, leading to better outcomes. AI can create social media ads tailored to specific demographics and preferences, ensuring that the content resonates with the target audience. With the help of an AI ad maker tool, businesses can efficiently produce high-quality advertisements that drive engagement and conversions across various social media platforms.

Personalization on a Large Scale

Personalization has always been important in marketing, and automation is making it possible on a larger scale. By using AI and machine learning, marketers can create tailored experiences for each customer based on their preferences, behaviors, and past interactions with the brand.

This level of personalization not only boosts customer satisfaction but also increases engagement and loyalty. When consumers feel understood and valued, they are more likely to become loyal customers and brand advocates. As automation technology continues to evolve, we can expect personalization to become even more advanced, enabling businesses to forge deeper connections with their audience. As your company has tiny homes for sale California, personalized experiences will ensure each customer finds their perfect fit, fostering lasting connections.

Integration Across Channels

Another trend shaping the future of marketing automation is the integration of multiple channels into a cohesive strategy. Today’s consumers interact with brands across various touchpoints, from social media and email to websites and mobile apps. Marketing automation platforms that can seamlessly integrate these channels and deliver consistent messaging will have a competitive edge. When creating a comparison website it’s important to ensure that the platform effectively aggregates data from diverse sources and presents it in a user-friendly manner, empowering consumers to make informed decisions.

Omni-channel integration not only betters the customer experience but also provides marketers with a comprehensive view of the customer journey. By tracking interactions across channels, businesses can gain valuable insights into how consumers engage with their brand, allowing them to refine their marketing strategies for maximum impact. Lastly, integrating SEO services into omni-channel strategies boosts visibility and helps businesses better understand and engage with their customers across different platforms.

The Human Element

While automation offers many benefits, it’s crucial not to overlook the human aspect of marketing. Despite advances in AI and machine learning, there are still elements of marketing that require human creativity, empathy, and strategic thinking.

Successful marketing automation strikes a balance between technology and human expertise. By using automation to handle routine tasks and data analysis, marketers can focus on what they do best – storytelling, building relationships, and driving innovation.

Conclusion

The future of marketing automation looks promising, offering improved efficiency and results for businesses of all sizes.

As AI continues to advance and consumer expectations change, automation will play an increasingly vital role in keeping businesses competitive.

By embracing automation technologies, marketers can simplify processes, deliver more personalized experiences, and ultimately, achieve their business goals more effectively than ever before.