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What part should marketing play?

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What part should marketing play?

If you have an artificial intelligence program, you also have a committee, team, or body that is providing governance over AI development, deployment, and use. If you don’t, one needs to be created.

In my last article, I shared the key areas for applying AI and ML models in marketing and how those models can help you innovate and meet client demands. Here I look at marketing’s responsibility for AI governance.

So, what is AI governance?

AI governance is what we call the framework or process that manages your use of AI. The goal of any AI governance effort is simple — mitigate the risks attached to using AI. To do this, organizations must establish a process for assessing the risks of AI-driven algorithms and their ethical usage.   

The stringency of the governance is highly dependent on industry. For example, deploying AI algorithms in a financial setting could have greater risks than deploying AI in manufacturing. The use of AI for assigning consumer credit scores needs more transparency and oversight than does an AI algorithm that distributes parts cost-effectively around a plant floor. 

To manage risk effectively, an AI governance program should look at three aspects of AI-driven applications:

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  • Data: What data is the algorithm using? Is the quality appropriate for the model? Do data scientists have access to the data needed? Will privacy be violated as part of the algorithm? (Although this is never intentional, some AI models could inadvertently expose sensitive information.) As data may change over time, it is necessary to consistently govern the data’s use in the AI/ML model.
  • Algorithms. If the data has changed, does it alter the output of the algorithm? For example, if a model was created to predict which customers will purchase in the next month, the data will age with each passing week and affect the output of the model. Is the model still generating appropriate responses or actions? Because the most common AI model in marketing is machine learning, marketers need to watch for model drift. Model drift is any change in the model’s predictions. If the model predicts something today that is different from what it predicted yesterday, then the model is said to have “drifted.”
  • Use. Have those that are using the AI model’s output been trained on how to use it? Are they monitoring outputs for variances or spurious results? This is especially important if the AI model is generating actions that marketing uses. Using the same example, does the model identify those customers who are most likely to purchase in the next month? If so, have you trained sales or support reps on how to handle customers who are likely to buy? Does your website “know” what to do with those customers when they visit? What marketing processes are affected as a result of this information?

How should it be structured and who should be involved?

AI governance can be structured in various ways with approaches that vary from highly controlled to self-monitored, which is highly dependent on the industry as well as the corporate culture in which it resides.  

To be able to direct to the model development as well as its validation and deployment, governance teams usually consist of both technical members who understand how the algorithms operate as well as leaders who understand why the models should work as they are planned. In addition, someone representing the internal audit function usually sits within the governance structure.  

No matter how AI governance is structured, the primary objective should be a highly collaborative team to ensure that AI algorithms, the data used by them and the processes that use the outcomes are managed so that the organization is compliant with all internal and external regulations.

Here is a sample AI Governance design for an organization taking a centralized approach, common in highly regulated industries like healthcare, finance, and telecommunications: 

Image: Theresa Kushner

What can marketers contribute to AI governance?

There are several reasons for marketing to be involved in the governance of AI models. All of these reasons relate to marketing’s mission. 

  1. Advocating for customers. Marketing’s job is to ensure that customers have the information they need to purchase and continue purchasing, as well as to evangelize for the company’s offerings. Marketing is responsible for the customers’ experiences and with protecting the customers’ information. Because of these responsibilities, the marketing organization should be involved in any AI algorithm that uses customer information or with any algorithm that has an impact on customer satisfaction, purchase behavior or advocacy.  
  1. Protecting the brand. One of marketing’s primary responsibilities is protecting the brand.  If AI models are being deployed in any way that might hurt the  brand image, marketing should step in. For example, if AI-generated credit worthiness scores are used to determine in advance which customers get the “family” discount, then marketing should be playing an important role in how that model is deployed. Marketing should be part of the team that decides whether the model will yield appropriate results or not. Marketing must always ask the question: “Will this situation change how our primary customers feel about doing business with us?”
  1. Ensuring open communications. One of the most often neglected areas of AI/ML model development and deployment is the storytelling that is required to help others understand what the models should be doing. Transparency and explicability are the two most important traits of good, governed AI/ML modeling. Transparency means that the models that are created are fully understood by those creating them and those using them as well as managers and leaders of the organizations. Without being able to explain what the model does and how it does it to the internal business leaders, the AI Governance team runs the huge risk of also not being able to explain the model externally to government regulators, outside counsels, or stockholders. Communicating the “story” of what the model is doing and what it means to the business is marketing’s job.
  1. Guarding marketing-deployed AI Models. Marketing should also be a big user of those AI/ML models that help determine which customers will purchase the most, which customers will remain customers the longest, and which of the most satisfied customers are likely to recommend you to other potential customers or indeed churn. In this role, marketing should have a seat at the AI Governance table to ensure that customer information is well managed, that bias does not enter the model and that privacy is maintained for the customer.  

Read next: AI and machine learning in marketing: Are you deploying the right models? 

But first, get to know the basics

I would like to say that your organization’s AI Governance will welcome marketers to the table, but it never hurts to be prepared and to do your homework. Here are a few skills and capabilities to familiarize yourself with before getting started: 

  • AI/ML understanding. You should understand what AI/ML are and how they work. This does not mean that you need a Ph.D. in data science, but it is a good idea to take an online course on what these capabilities are and what they do. It’s most important that you understand what impact should be expected from the models especially if they run the risk of exposing customer information or putting the organization at financial or brand risk.
  • Data. You should be well-versed in what data is being used in the model, how it was collected and how and when it is updated. Selecting and curating the data for an AI model is the first place where bias can enter the algorithm. For example, if you are trying to analyze customer behavior around a specific product, you will usually need about three-quarters of data collected in the same way and curated so that you have complete as well as accurate information. If it’s marketing data that the algorithm will be using, then your role is even more important.
  • Process. You should have a good understanding of the process in which the algorithm will be deployed. If you are sitting on the AI Governance team as a marketing representative and the AI algorithms being evaluated are for sales, then you should familiarize yourself with that process and how and where marketing may contribute to the process. Because this is an important skill to have if you serve on the AI Governance team, many marketing teams will appoint the marketing operations head as their representative.

No matter what role you play in AI Governance, remember how important it is. Ensuring that AI/ML is deployed responsibly in your organization is not only imperative, but also an ongoing process, requiring persistence and vigilance, as the models continue to learn from the data they use.  


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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


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About The Author

5 steps to make the most of your reporting and

Theresa Kushner is passionate about data analysis and how it gets applied to today’s business challenges. For over 25 years she has led companies – like IBM, Cisco Systems, VMware, Dell/EMC – in recognizing, managing, and using the information or data that has exploded exponentially. Using her expertise in journalism, she co-authored two books on data and its use in business: Managing Your Business Data: From Chaos to Confidence (with Maria Villar) and B2B Data-Driven Marketing: Sources, Uses, Results
(with Ruth Stevens). Today, as the Data and Analytics practice lead for NTT DATA, Theresa continues to help companies – and their marketing departments — gain value from data and information.

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Ecommerce evolution: Blurring the lines between B2B and B2C

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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)

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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.” 

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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. 

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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.

Related: Redefining personalization for B2B commerce

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. 

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Streamlining Processes for Increased Efficiency and Results

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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.

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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

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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.  

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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.

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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.

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Will Google Buy HubSpot? | Content Marketing Institute

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Why Marketers Should Care About Google’s Potential HubSpot Acquisition

Google + HubSpot. Is it a thing?

This week, a flurry of news came down about Google’s consideration of purchasing HubSpot.

The prospect dismayed some. It delighted others.

But is it likely? Is it even possible? What would it mean for marketers? What does the consideration even mean for marketers?

Well, we asked CMI’s chief strategy advisor, Robert Rose, for his take. Watch this video or read on:

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Why Alphabet may want HubSpot

Alphabet, the parent company of Google, apparently is contemplating the acquisition of inbound marketing giant HubSpot.

The potential price could be in the range of $30 billion to $40 billion. That would make Alphabet’s largest acquisition by far. The current deal holding that title happened in 2011 when it acquired Motorola Mobility for more than $12 billion. It later sold it to Lenovo for less than $3 billion.

If the HubSpot deal happens, it would not be in character with what the classic evil villain has been doing for the past 20 years.

At first glance, you might think the deal would make no sense. Why would Google want to spend three times as much as it’s ever spent to get into the inbound marketing — the CRM and marketing automation business?

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At a second glance, it makes a ton of sense.

I don’t know if you’ve noticed, but I and others at CMI spend a lot of time discussing privacy, owned media, and the deprecation of the third-party cookie. I just talked about it two weeks ago. It’s really happening.

All that oxygen being sucked out of the ad tech space presents a compelling case that Alphabet should diversify from third-party data and classic surveillance-based marketing.

Yes, this potential acquisition is about data. HubSpot would give Alphabet the keys to the kingdom of 205,000 business customers — and their customers’ data that almost certainly numbers in the tens of millions. Alphabet would also gain access to the content, marketing, and sales information those customers consumed.

Conversely, the deal would provide an immediate tip of the spear for HubSpot clients to create more targeted programs in the Alphabet ecosystem and upload their data to drive even more personalized experiences on their own properties and connect them to the Google Workspace infrastructure.

When you add in the idea of Gemini, you can start to see how Google might monetize its generative AI tool beyond figuring out how to use it on ads on search results pages.

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What acquisition could mean for HubSpot customers

I may be stretching here but imagine this world. As a Hubspoogle customer, you can access an interface that prioritizes your owned media data (e.g., your website, your e-commerce catalog, blog) when Google’s Gemini answers a question).

Recent reports also say Google may put up a paywall around the new premium features of its artificial intelligence-powered Search Generative Experience. Imagine this as the new gating for marketing. In other words, users can subscribe to Google’s AI for free, but Hubspoogle customers can access that data and use it to create targeted offers.

The acquisition of HubSpot would immediately make Google Workspace a more robust competitor to Microsoft 365 Office for small- and medium-sized businesses as they would receive the ADDED capability of inbound marketing.

But in the world of rented land where Google is the landlord, the government will take notice of the acquisition. But — and it’s a big but, I cannot lie (yes, I just did that). The big but is whether this acquisition dance can happen without going afoul of regulatory issues.

Some analysts say it should be no problem. Others say, “Yeah, it wouldn’t go.” Either way, would anybody touch it in an election year? That’s a whole other story.

What marketers should realize

So, what’s my takeaway?

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It’s a remote chance that Google will jump on this hard, but stranger things have happened. It would be an exciting disruption in the market.

The sure bet is this. The acquisition conversation — as if you needed more data points — says getting good at owned media to attract and build audiences and using that first-party data to provide better communication and collaboration with your customers are a must.

It’s just a matter of time until Google makes a move. They might just be testing the waters now, but they will move here. But no matter what they do, if you have your customer data house in order, you’ll be primed for success.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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