Better Customer Insights: The Power of Personalization

One of the most significant ways AI revolutionizes marketing is by enhancing customer insights. Traditionally, marketers have relied on broad demographics and basic analytics to understand their audience. However, AI allows for a much deeper dive into customer behavior, preferences, and future actions.

“When I first got into AI marketing, I imagined it like having a crystal ball,” says a seasoned AI marketer. “But it’s more like having a supercharged assistant. It analyzes mountains of data faster than any human and gives us insights we couldn’t see before.” This capability enables marketers to tailor their messages with unprecedented precision, creating what feels like a personal conversation with each customer.

The impact is profound. By leveraging AI, companies can move beyond generic marketing strategies to deliver highly personalized content that resonates on an individual level. This is no longer about guessing what a customer might want; it’s about predicting it with a high degree of accuracy. “With AI, we understand our customers on a deeper level. It looks at patterns, preferences, and predicts behaviors,” another marketer explains. “This means we can tailor our messages so they hit just right.”

Optimizing Ad Spend: Getting More Bang for the Buck

In an era where every marketing dollar counts, AI is helping companies optimize their ad spend like never before. The days of broad, expensive campaigns with uncertain returns are fading. AI-driven platforms now enable marketers to pinpoint exactly where their ads will be most effective, and even the best times to deploy them.

“AI helps us squeeze more out of every dollar,” a marketing executive from a leading firm shares. “It identifies where our ads perform best and even suggests the perfect times to post. Imagine knowing with confidence that your budget is always working the hardest.” This optimization isn’t just a slight improvement—it’s a game changer in how marketing strategies are formulated and executed.

For Fortune 5000 companies, this capability means the difference between a scattergun approach and a laser-focused strategy that ensures maximum ROI. As marketing budgets continue to tighten, the ability to stretch those dollars further is not just beneficial—it’s essential for survival.

Personalization at Scale: The New Reality

Personalization has long been a buzzword in marketing circles, but with AI, it’s now a tangible reality. Historically, creating personalized experiences for customers was labor-intensive and feasible only on a small scale. AI changes that, allowing companies to deliver tailored experiences to millions of customers without the need for massive human intervention.

“AI allows us to create individual experiences for millions without breaking a sweat. It’s like having a personal shopper for each customer, but digital,” a marketer quips. This level of personalization at scale was once unimaginable, but it’s quickly becoming the norm in the AI-powered marketing world.

For large corporations, this means they can maintain a personal touch with their customers even as they grow. The ability to personalize interactions on a massive scale not only improves customer satisfaction but also drives loyalty and repeat business—key metrics in the success of any marketing strategy.

Predicting Trends: Staying Ahead of the Curve

One of the most powerful aspects of AI in marketing is its ability to predict trends. Marketers have always sought to be ahead of the curve, but trend prediction has traditionally been more art than science. AI changes that dynamic by analyzing vast amounts of data to identify subtle shifts that could indicate the next big trend.

“No more guessing which trend is next,” a marketing director from a tech giant remarks. “AI scrapes through endless data and picks up on small shifts before they become big waves. It’s like having a trend-spotter who never sleeps.” This predictive capability allows companies to react to trends and anticipate and capitalize on them before their competitors do.

For the Fortune 5000, this means staying relevant in an increasingly fast-paced market. The ability to foresee shifts in consumer behavior or emerging market trends gives these companies a significant competitive edge. In industries where timing is everything, the foresight provided by AI can be the difference between leading the market and playing catch-up.

The Human Element: Enhancing Creativity and Empathy

Despite all the advancements AI brings to the table, there remains a critical human element that machines cannot replicate: creativity and empathy. While AI can analyze data and predict behaviors, it’s up to human marketers to interpret these insights and craft campaigns that connect on an emotional level.

“The magic here isn’t just in tech; it’s in how we use it. We’ve got to stay curious and keep asking questions,” says a veteran marketer. “AI won’t replace our creativity and empathy; it’ll just make them shine brighter.” This perspective underscores the importance of maintaining a human touch in an increasingly automated world.

For marketers, this means using AI as a tool to enhance their work, not replace it. The combination of AI’s analytical power with human creativity is what will ultimately drive the most successful marketing strategies. It’s about being more human, not less, in a world where technology is becoming more pervasive.

AI as an Ally

As AI continues to integrate into the marketing world, it’s clear that it’s not a threat but an ally to those who know how to harness its power. For Fortune 5000 marketers, AI offers a suite of tools that can help them better understand their customers, optimize their budgets, personalize at scale, and predict trends with unparalleled accuracy.

“Whether you’re a marketer in a giant corporation or a small start-up, remember: AI is your ally. Use it to be more human, not less,” a marketing thought leader advises. This mindset will be crucial as AI becomes more embedded in the fabric of marketing strategies across the globe.

In the end, AI is not about replacing marketers; it’s about empowering them to do their jobs better. For the Fortune 5000, this means embracing AI not as a threat but as the next evolution in marketing—a tool that, when used correctly, can lead to smarter decisions, more effective campaigns, and ultimately, greater success in an increasingly competitive market.

A Crisis of Ownership

Kris Holland, a futurist, seasoned artist, and owner of Mafic Studios, Inc., has been vocal about the dangers generative AI poses to the art world. His concerns center around the erosion of ownership and control over artistic creations. “My art is mine; while the ideas behind it are subject to inspiration and use by others, my embodiment is mine,” Holland insists. His perspective highlights a fundamental clash between traditional notions of intellectual property and the way AI algorithms operate. Generative AI models, trained on vast datasets of existing artwork, can produce new images that mimic the styles of countless artists without their consent or recognition.

You’ve got to admit Kris Holland has a valid point. Read his many posts on this subject on LinkedIn, which inspired this article.

This conflict over ownership is exacerbated by outdated copyright laws, which, as Holland points out, are often manipulated by large corporations to their advantage. “We live in a reality where I don’t own my art, creations, or text. No matter what the ethical and moral stance I might have,” he laments. The result is a chilling scenario where artists like Holland find themselves increasingly sidelined by a technology that can replicate their work without attribution or compensation.

The Ethical Dilemma

The ethical implications of generative AI extend far beyond individual artists’ grievances. The technology’s ability to replicate art raises questions about authenticity, creativity, and the very definition of art itself. Holland describes generative AI as a “mathematical transformation based on a complex matrix,” arguing that it lacks the intentionality that characterizes true artistic expression. “Art is intentional on the part of the artist, independent of skill. While there are inevitably happy accidents, experimentation, and so forth, the human is 99.9% of the required effort for a result to have any meaning,” he explains.

This perspective challenges the notion that AI-generated art can ever be considered equivalent to human-made art. While AI can produce visually appealing images, Holland contends that it does so without the depth of thought, emotion, and intent that human artists bring to their work. As a result, he fears that the proliferation of AI-generated art will lead to a “tidal wave of crap”—a deluge of aesthetically pleasing but ultimately meaningless images that drown out the genuine creativity of human artists.

A Dystopian Future for Art?

Holland’s concerns are not just theoretical. He warns that the widespread adoption of generative AI could lead to a future where new art becomes increasingly rare, with most creative output consisting of derivative works produced by algorithms. “After a few years, there will be very little new art. All we’ll have is billions of generated images that are somewhat better than what we have today but decidedly similar to everything else,” he predicts. This homogenization of art, driven by AI’s reliance on existing data, could stifle innovation and reduce the cultural significance of art in society.

The potential for generative AI to displace artists is not lost on Holland. He notes that many artists, particularly those working in commercial fields, are already feeling the impact. “I got into commercial art knowing that I had some degree of control—the idea that my art, my effort, could be dismantled and used to compete with me wasn’t something that could be done,” he recalls. Now, however, artists are finding it increasingly difficult to protect their work from being co-opted by AI, leading some, like Holland, to consider leaving the field altogether.

Corporate Greed and the Loss of Human Creativity

At the heart of the issue, Holland argues, is the greed of the corporations driving the development of generative AI. “Corporations will set fire to the future if it improves the next quarter’s EBITDA,” he asserts. The relentless pursuit of profit, he believes, has led these companies to disregard the rights of artists and the value of human creativity. Instead of investing in ethical AI that respects intellectual property, they have adopted a “do what we want, and leverage our money to change the rules” approach, further marginalizing the artists whose work they exploit.

Holland’s critique extends to the broader societal implications of generative AI. He warns that the technology is not just threatening individual artists but is also eroding the cultural fabric of society. “This is not about technology. It’s about corporate greed steamrolling humanity’s soul,” he declares. By reducing art to a mere commodity that can be mass-produced by machines, generative AI undermines the role of art as a means of human expression and cultural preservation.

A Call for Ethical AI

Despite his deep concerns, Holland does not reject technology outright. Instead, he advocates for a more ethical approach to AI development—one that prioritizes the rights and interests of creators. He envisions a future where AI tools are built from ethically sourced datasets, with full traceable permission from the original creators. “I believe the tool version can be built from a fully ethically sourced dataset. Due to limited subjects, the result would be less capable to start, but evolve quickly,” he suggests.

Holland’s proposed solution involves creating massive datasets of ethically sourced images, captured with the explicit consent of the subjects. This approach, he argues, would allow AI to develop in a way that respects the rights of creators while still providing valuable tools for enhancing productivity. “With a single system, I could capture over 50,000,000 photos a year with a single setup,” he notes, emphasizing the feasibility of his ethical AI model.

A Path Forward

As the debate over generative AI continues, artists like Kris Holland are calling for a more balanced approach—one that recognizes the potential of AI while safeguarding the rights and livelihoods of human creators. The challenge lies in finding a path forward that allows technology and art to coexist without diminishing the value of human creativity.

Holland’s insights underscore the need for a broader societal conversation about the role of AI in the arts. As generative AI becomes increasingly integrated into creative industries, it is essential to address the ethical, legal, and cultural issues it raises. By doing so, we can ensure that technology enhances, rather than undermines, the rich tapestry of human creativity that has defined art for centuries.

In the end, the question remains: Can we harness the power of generative AI without sacrificing the soul of art? The answer will depend on the choices we make today—and the future we envision for the artists of tomorrow.

While much of the discourse around AI has been focused on its potential, the conversation is shifting from what AI can do to how it can be effectively integrated into real-world B2B use cases. As companies strive to stay competitive, the adoption of GenAI is moving from a futuristic concept to a practical necessity. But as with any powerful tool, the challenge lies in understanding how to leverage it for tangible business results.

From Hype to Implementation: The Need for Practical AI Strategies

The buzz around AI has been impossible to ignore. Terms like large language models (LLMs) and prompt engineering have become commonplace, yet many B2B marketers are still grappling with how to apply these concepts in a meaningful way. Christopher Penn, Co-Founder and Chief Data Scientist at TrustInsights.ai, encapsulates this sentiment. “Tired of hearing about AI and LLMs without knowing how to actually use them in your B2B marketing?” Penn’s question resonates with many in the industry who are inundated with AI jargon but lack practical guidance on implementation.

Penn’s upcoming presentation at the MarketingProfs B2B Forum aims to bridge this gap. His focus is on moving beyond theoretical discussions and diving into actionable strategies that marketers can use today. “We’ll cover the fundamentals of prompting, demystify how Large Language Models work, and explore advanced strategies like the Trust Insights PARE and RACE frameworks for creating semi-autonomous prompts,” he explained. These frameworks are designed to help marketers craft prompts that allow for automation while retaining control over the output—striking a balance between efficiency and oversight.

Competitive Analysis: Uncovering Hidden Opportunities

One of the most compelling applications of GenAI in B2B marketing is its ability to revolutionize competitive analysis. The process of gathering competitive intelligence is often labor-intensive, requiring marketers to sift through vast amounts of data to glean actionable insights. GenAI, however, can automate much of this work, uncovering hidden competitor strategies that might otherwise go unnoticed. Penn highlights this as a critical use case, noting, “Imagine uncovering hidden competitor strategies or identifying the perfect micro-influencer for your next campaign—all through the power of well-crafted prompts.”

This capability represents a significant advancement in how B2B marketers can approach competitive analysis. Traditional methods often involve manual research, which can be both time-consuming and prone to human error. GenAI, by contrast, can process vast datasets in a fraction of the time, identifying patterns and insights that provide a competitive edge. This not only enhances strategic decision-making but also allows companies to react more quickly to changes in the market.

Influencer Alignment: Targeting Precision in B2B Campaigns

In addition to competitive analysis, Penn also emphasizes the role of GenAI in influencer alignment. Identifying the right influencers who resonate with your target audience is a critical challenge in B2B marketing, where the stakes are often higher than in B2C campaigns. GenAI can streamline this process by analyzing large datasets to match brands with influencers whose audiences align with the brand’s objectives. This level of precision ensures that marketing efforts are not only effective but also highly targeted.

“GenAI can simplify the process by analyzing vast amounts of data to match brands with influencers whose audiences align with the brand’s goals,” Penn explained. This capability is particularly valuable in B2B marketing, where the target audience is often more niche, and the relationships between brands and influencers need to be carefully cultivated. By automating the data analysis process, GenAI allows marketers to focus on building these relationships rather than spending countless hours on manual research.

Content Creation: Beyond Automation

While content creation is often the most discussed application of GenAI, Penn is quick to point out that its utility extends far beyond generating blog posts or social media updates. “This isn’t just about content creation,” he said. “We’ll be tackling real-world B2B use cases like competitive analysis, strategic planning, and influencer alignment.”

The real power of GenAI in content creation lies in its ability to support higher-level strategic tasks. For instance, by automating the initial stages of content generation, GenAI frees up marketers to focus on refining messaging, optimizing campaigns, and developing more sophisticated marketing strategies. This shift from manual content production to strategic oversight is where GenAI offers the most value, allowing companies to scale their content efforts without sacrificing quality.

Strategic Planning: Aligning AI with Business Goals

Effective use of GenAI in B2B marketing requires more than just technical know-how; it necessitates a strategic approach that aligns AI initiatives with broader business goals. As Penn noted, “You want to have a top-down approach to this. You want to make sure that you’re identifying that early use case, rolling it out as a team, and again, talking about those standards and the ways that your team is going to actually realize the results of that AI use.”

This top-down approach ensures that AI initiatives are not just experiments conducted in isolation but are integrated into the company’s overall strategy. It also helps mitigate risks by establishing clear standards and protocols for AI use across the organization. By aligning AI initiatives with business objectives, companies can ensure that their investments in GenAI are driving real value.

Meghan Keaney Anderson, VP of Marketing at Jasper, echoed this sentiment during a recent LinkedIn fireside chat. “The strategy that you have as a marketing team, it’s going to fundamentally change in a significant way over the next few years, not just by using AI tools, but because of the way that AI is going to change things like search and the way that people discover and consume content,” she said. This shift underscores the importance of strategic planning in AI adoption, ensuring that companies are prepared for the broader changes that AI will bring to the marketing landscape.

Navigating the Challenges of AI Integration

Despite the clear benefits of GenAI, its integration into B2B marketing strategies is not without challenges. One of the most significant hurdles is balancing experimentation with control. As Penn observed, “Either there’s a ton of experimentation happening, and it’s happening at the individual level. That means there may be some risk because individuals may be using or using tools that aren’t secure or are using them incorrectly. Or the company is completely locked down, and no experimentation is happening at all.”

Penn advocates for a structured, top-down approach that encourages experimentation within a controlled environment to navigate this challenge. “You want to have a top-down approach to this,” he advised. “You want to make sure that you’re identifying that early use case, rolling it out as a team, and again, talking about those standards and the ways that your team is going to actually, you know, realize the results of that AI use.”

This approach ensures that experimentation is guided by clear objectives and aligned with the company’s overall strategy. It also helps mitigate risks associated with AI deployment by establishing standards and protocols for AI use across the organization. By creating a controlled environment for experimentation, companies can explore the full potential of GenAI while minimizing the risks associated with its use.

Upskilling and Education: Preparing Teams for AI Integration

As companies integrate GenAI into their marketing strategies, their teams must be equipped to leverage these new tools effectively. Penn highlighted the importance of upskilling and continuous education in this process. “Invest in AI education,” he recommended. “LinkedIn has a ton of really good educational content around AI right now. Sign your employees, your team up for those, have discussions about them. There are incredible things that AI can do. There are also a lot of weaknesses of AI. Make sure that your team knows what goes on behind the scenes of this technology and demystify it a bit.”

This focus on education is essential for ensuring that teams are not only able to use AI tools but also understand their limitations. By providing ongoing training and development opportunities, companies can ensure that their teams are prepared to navigate AI’s challenges and opportunities. This approach also helps to foster a culture of continuous learning, which is critical for staying competitive in the fast-paced world of B2B marketing.

Measurement and ROI: Moving Beyond Efficiency

In the early stages of AI adoption, much of the focus has been on efficiency—how AI can help companies do more with less. However, as Penn pointed out, the true value of AI lies in its ability to drive better business outcomes. “The whole discussion in the first year of mass adoption of AI was all about efficiency. How do we use AI to cut costs? How did we use AI to do more with less? And efficiency is great, but I think if that’s the end of the story, it’s sort of an underwhelming output of AI,” he said.

Penn advocates for a shift in focus from efficiency to effectiveness. “We have to get beyond faster outputs into better outcomes for marketing materials,” he argued. This means using AI not just to save time but to improve the quality of marketing efforts, drive better results, and ultimately contribute to the company’s bottom line.

The Future of B2B Marketing with GenAI

As GenAI continues to evolve, its impact on B2B marketing is expected to grow. Anderson emphasized that the changes we’re seeing now are just the beginning. “The strategy that you have as a marketing team, it’s going to fundamentally change in a significant way over the next few years, not just by using AI tools, but because of the way that AI is going to change things like search and the way that people discover and consume content,” she said.

Looking ahead, GenAI’s potential applications in B2B marketing are massive. From automating repetitive tasks to enabling hyper-personalization at scale, AI offers marketers new ways to enhance their strategies and deliver more value to their clients. However, success will depend on marketers’ ability to navigate the challenges of AI integration, including managing risks, aligning AI initiatives with broader business goals, and ensuring that their teams can effectively leverage these powerful tools.

B2B Marketers Are at a Critical Juncture

As the adoption of GenAI accelerates, B2B marketers are at a critical juncture. The promise of AI is no longer just theoretical—it’s a practical reality that can drive real business results. However, realizing this potential requires a strategic approach that goes beyond experimentation and focuses on alignment with broader business objectives.

By leveraging GenAI for competitive analysis, strategic planning, and influencer alignment, marketers can unlock new levels of efficiency and effectiveness. But to fully capitalize on the potential of GenAI, companies must invest in upskilling their teams, creating a culture of continuous learning, and focusing on driving better business outcomes rather than just improving efficiency.

As Penn aptly put it, “Learn to leverage the power of AI to drive real results for your business.” With the right strategies in place, GenAI has the potential to revolutionize B2B marketing, helping companies stay ahead of the competition and deliver more value to their clients. The future of B2B marketing is here, and it’s powered by AI.

The AI Tell: Over-Formalization and Buzzword Overload

One of the first signs that you might be channeling your inner ChatGPT is the use of overly formal language or an excessive reliance on buzzwords. Words like “synergy,” “innovation,” and “ever-evolving” might sound polished, but they also scream, “I was generated by an algorithm.” As Daniel Kenitz humorously pointed out, “In the ever-evolving world of talking like this, one person stands out: me.” The key takeaway here is that while these words can be useful, overusing them or inserting them into every sentence can make your writing feel disingenuous.

Jeffery Nicolaysen, a seasoned writer, shared a poignant observation on this topic: “How dystopian is it that competent writing is now assumed to be AI, eloquence and precision of language are frowned upon, and any form of complex sentence structure is assumed to be run-on?” The concern is real—good writing should feel organic, not forced or formulaic.

Avoiding the “AI-Tone”

To avoid sounding like a machine, one must steer clear of the “AI tone”—a tone that tends to be overly neutral and lacks personality. While AI can generate well-structured sentences, it often lacks the nuanced flair that makes human writing stand out. “It’s funny that professional work society created this weirdly specific and laughably over-the-top ‘professional’ way of writing,” said Trevor Merrill, highlighting the absurdity of the rigid, AI-like writing style.

Injecting your unique voice into your writing is crucial. This can be achieved by:

1. Using Contractions: Don’t be afraid to use contractions like “don’t,” “won’t,” and “you’re.” These small changes can make your writing feel more conversational and less robotic.
2. Adding Personal Touches: Use anecdotes, humor, or even a bit of sarcasm where appropriate. Daniel Kenitz himself demonstrated this by inviting ChatGPT to help with a line and then humorously attributing the overly formal result to the AI.
3. Engaging Directly with Your Audience: Phrases like “Let’s dive into this” or “Here’s what you need to know” bring a conversational tone that is harder for AI to replicate authentically.

The Pitfalls of Predictability

Another giveaway that you might be relying too heavily on AI-generated content is predictability. AI tends to stick to tried-and-true patterns, which can lead to repetitive and uninspired writing. Kristine Cain noted that terms like “ever-evolving” are often dead giveaways of AI influence. This predictability can be avoided by:

• Mixing Up Sentence Structures: Avoid falling into a repetitive rhythm by varying your sentence length and structure. Combine short, punchy sentences with longer, more complex ones.
• Breaking the Mold: Don’t be afraid to stray from the conventional. Inject a surprising fact, a rhetorical question, or a bold statement to keep your readers engaged.

The Human Advantage: Emotion and Empathy

What AI still struggles with is capturing the full spectrum of human emotion and empathy. As Salwa Emerson eloquently put it, “We cannot measure with numbers the arcs of self-discovery that intersect between two hearts.” This depth of emotion is what makes human writing resonate on a deeper level.

To ensure your writing has that human touch, focus on:

• Expressing Genuine Emotion: Whether it’s excitement, frustration, or curiosity, let your true feelings guide your writing.
• Empathizing with Your Audience: Understand the concerns, desires, and challenges of your audience. Speak directly to those emotions in your content.

Embrace Your Human Voice

In a world where AI-generated content is becoming increasingly common, it’s more important than ever to embrace and preserve your unique human voice. As Maree Gately points out, “No one talks like that. Plus, it doesn’t make sense.” The challenge—and the opportunity—lies in creating content that is not only technically sound but also rich in personality, emotion, and authenticity.

So the next time you sit down to write, remember to keep it real. Use humor, mix up your sentence structures, and most importantly, write in a way that sounds like you—not an AI. Because at the end of the day, it’s your unique perspective and voice that will truly engage your readers. As Daniel Kenitz cheekily concludes, “Synergy and innovation are at the core of my conversational strategy”—and so is being unmistakably human.

• Enhance customer understanding.
• Optimize operational efficiency.
• Obtain competitive advantages.  

If we’re talking about these things, we imagine the wow effect of the integration scenario that automatically syncs customer relationship management (CRM) data, like marketing metrics, sales activities, and customer service interactions, into BigQuery for advanced analytics, reporting, and data-driven decision-making. Here, businesses found a big brilliant like BigQuery’s analytic abilities to receive deeper insights from HubSpot data, enhance strategic planning, and optimize marketing and sales with data analysis.

Why Businesses Need HubSpot to BigQuery Integration 

Businesses may need to integrate HubSpot and bigQuery mostly while thinking about enhancing their data analytics, reporting abilities, and decision-making processes. Let’s review the set of reasons closely.

Advanced Analytics and Reporting

Businesses that want to analyze their marketing, sales, or customer service data may use the native capabilities of HubSpot to benefit from this integration. At the same time, BigQuery allows combining HubSpot data with other data sources for comprehensive reporting and analytics.

Customer Behavior Insights

Integrating the HubSpot data into Big Query is ideal for companies looking to understand customer behavior across different touchpoints to analyze customer interactions, campaign effectiveness, and conversion paths, meaning more targeted marketing strategies.

Scalable Data Storage Needs

As businesses grow, so does their data. BigQuery provides a scalable solution for storing vast amounts of HubSpot-generated data, ensuring businesses can maintain and analyze historical data without performance issues.

Real-time Data Processing

For companies that require real-time analytics to make quick decisions, integrating HubSpot with BigQuery can provide the necessary infrastructure to process data as it comes in, providing timely insights and actions.

Data Centralization for BI Tools

 Integrating HubSpot with BigQuery also benefits companies that use Business Intelligence (BI) tools for data visualization and dashboards. This process centralizes data, making creating comprehensive reports that include CRM data alongside other business metrics easier.

Cross-functional Data Analysis

When departments like marketing, sales, and customer service need to collaborate and share insights, integrating HubSpot data into BigQuery provides cross-functional analysis, helping align strategies and goals across the organization.

Compliance and Data Governance

BigQuery’s robust data governance and security features help ensure compliance with regulations like GDPR.

Machine Learning and Predictive Analytics

Machine learning allows companies to use predictive marketing and sales data analytics to leverage BigQuery’s ML abilities. By integrating HubSpot data, businesses can build predictive models to forecast trends, customer behavior, and campaign performance.

Pitfalls and Mitigations of HubSpot to BigQuery Integration

HubSpot and Google BigQuery integration offers many advantages but also has potential pitfalls. Users must understand these challenges and how to mitigate them for a successful integration. 

The table below displays common pitfalls and strategies for addressing them.

Business Scenarios and Examples

Integrating HubSpot with Google BigQuery may unlock a set of cool capabilities for businesses across various scenarios, allowing firms to use their data for personalized customer experiences, insights, and data-driven decision-making. Let’s walk through the examples of the most common scenarios.

• Comprehensive Marketing Analytics
• Personalized Customer Journeys
• Real-time Reporting and Dashboards
• Customer Segmentation and Targeting
• Compliance and Data Governance
• Optimizing Customer Support

Conclusion

Integrating HubSpot into BigQuery unlocks the power of both platforms. It is the ideal solution for businesses that prefer data-driven decisions and use advanced data analytics abilities to obtain competitive advantages, enhance customer understanding, and optimize daily routines.

Alexis Zamkow, the Global Offering Leader for Intelligent Marketing at IBM, is at the forefront of this paradigm shift. With a keen understanding of marketing strategy and technological innovation, Zamkow spearheads efforts to harness the power of Generative AI to drive exceptional performance for businesses worldwide.

In a recent address at the AI Academy on the IBM Technology YouTube channel, Zamkow delved into the profound implications of Generative AI for the marketing industry. Drawing parallels to glass’s transformative journey, she emphasized the pivotal role of technology in elevating ordinary sand into extraordinary creations.

“For marketers, that moment of discovery and transformation is right now, with the arrival of Generative AI,” Zamkow declared, setting the stage for a compelling exploration of this groundbreaking technology.

As Zamkow elucidated, Generative AI promises to revolutionize marketing across two key dimensions: content creation and personalization. Leveraging advanced algorithms and multimodal models, Generative AI empowers marketers to generate diverse content, from marketing blogs to web banners, with unprecedented speed and efficiency.

The implications of this capability are profound, particularly for large enterprises with complex brand identities and product portfolios. By training Generative AI models to understand their brand nuances, companies can streamline the creative process and scale content production to meet the demands of today’s dynamic market landscape.

Yet, the true potential of Generative AI lies in its ability to personalize marketing messages at scale. By analyzing vast troves of data and identifying patterns and preferences, Generative AI enables marketers to deliver hyper-personalized experiences tailored to individual customers.

Zamkow illustrated this potential with a compelling example of how Generative AI could transform customer interactions in real-time. From addressing complaints to crafting personalized offers, Generative AI empowers marketers to engage with customers in ways that were previously unimaginable.

However, Zamkow also emphasized the importance of responsible AI governance and data management. As companies embrace Generative AI, they must prioritize security, privacy, and ethical considerations to ensure customer trust remains paramount.

As Zamkow concluded her talk, she left her audience with a call to action: to embrace the transformative potential of Generative AI and embark on a journey of exploration and innovation. With the right combination of strategy, technology, and creativity, marketers can harness the power of Generative AI to unlock new possibilities and drive lasting success in the digital age.

Rob Locascio, CEO of LivePerson, predicts that the AI-driven conversational space will ultimately have as much impact and be as big an industry as ecommerce, search, or social. Locascio was interviewed by Jim Cramer on CNBC:

Ecommerce, Search, Social… and Conversational Space?

When I look at the conversational space I think it’s going to have as much impact as ecommerce or search or social. The ability to talk to a machine and have a natural conversation, it’s in the collective consciousness of people. We all believe the Alexa type situation should happen with every company. 

We do that with Delta and T-Mobile and all these big brands. What we’re looking at now is how do we take that to the world? LiveIntent is proprietary technology to look at the intent that a consumer is having with the brand. In terms of I want to buy something, we have a way to analyze that and then use machine learning algorithms to then scale those conversations. That’s what this is about. 

Healthcare Companies Defending Themselves From Amazon Via AI

In Q4 we signed a couple healthcare companies. They want to talk about defending themselves from Amazon because Amazon said they want to go into healthcare. The way they think they can do that is scaling the conversations they are having with their customers and creating a totally different experience. You go to a doctor, you have an experience with them, you capture that on a messaging platform and an AI will help you with whatever is wrong with you. You want to process a bill instead of calling and being put on hold, you do that through a conversational experience. 

They want to game change it. The only way they’re going to defend themselves is to get into the conversational space. That’s what they see and we’re the company they’re trusting to scale their operations with the conversational platform.

Conversational Space Is Going To Be As Big As Search and Social

The conversational space is going to be as big as search and social. I think you’ll see one day that there will be a trillion dollar company in this space and I want it to be us. The things we’re investing in right now and setting up for will allow us to do that. That’s what’s important. The Amazon’s and the Facebook’s and Apple’s, they’re in the space. Jeff Bezos made a big bet obviously in Alexa to say this is the way it’s going to be. 

It can’t just be Amazon and Alexa. It has to be other companies getting access to that technology and that’s what we are providing. Who else is providing it? We’re one of the largest companies in the world to do this. Even though we’re not big tech, we are large enough to go ahead and go after them. We are large enough to go ahead and define a space and win it.

Rob Locascio, CEO of LivePerson, predicts that the AI-driven conversational space will ultimately have as much impact and be as big an industry as ecommerce, search, or social. Locascio was interviewed by Jim Cramer on CNBC:

Ecommerce, Search, Social… and Conversational Space?

When I look at the conversational space I think it’s going to have as much impact as ecommerce or search or social. The ability to talk to a machine and have a natural conversation, it’s in the collective consciousness of people. We all believe the Alexa type situation should happen with every company. 

We do that with Delta and T-Mobile and all these big brands. What we’re looking at now is how do we take that to the world? LiveIntent is proprietary technology to look at the intent that a consumer is having with the brand. In terms of I want to buy something, we have a way to analyze that and then use machine learning algorithms to then scale those conversations. That’s what this is about. 

Healthcare Companies Defending Themselves From Amazon Via AI

In Q4 we signed a couple healthcare companies. They want to talk about defending themselves from Amazon because Amazon said they want to go into healthcare. The way they think they can do that is scaling the conversations they are having with their customers and creating a totally different experience. You go to a doctor, you have an experience with them, you capture that on a messaging platform and an AI will help you with whatever is wrong with you. You want to process a bill instead of calling and being put on hold, you do that through a conversational experience. 

They want to game change it. The only way they’re going to defend themselves is to get into the conversational space. That’s what they see and we’re the company they’re trusting to scale their operations with the conversational platform.

Conversational Space Is Going To Be As Big As Search and Social

The conversational space is going to be as big as search and social. I think you’ll see one day that there will be a trillion dollar company in this space and I want it to be us. The things we’re investing in right now and setting up for will allow us to do that. That’s what’s important. The Amazon’s and the Facebook’s and Apple’s, they’re in the space. Jeff Bezos made a big bet obviously in Alexa to say this is the way it’s going to be. 

It can’t just be Amazon and Alexa. It has to be other companies getting access to that technology and that’s what we are providing. Who else is providing it? We’re one of the largest companies in the world to do this. Even though we’re not big tech, we are large enough to go ahead and go after them. We are large enough to go ahead and define a space and win it.

Shantanu Narayen, Chairman and CEO of Adobe, discusses how the pandemic has created another “inflection point” in the move toward digital transformation:

Digital Transformation Is A $120 Billion Opportunity

It was a good quarter all around. All of our businesses performed exceedingly well. On the Creative Cloud and the Document Cloud, not only did we have a great acquisition. in other words, new customers adopting the platform, but we really focused on engagement and demonstrating the value of our products to our customers. Even our retention levels came back to pre-COVID levels which we believe is a really good sign.

What’s happening in the world is the businesses that we’re in, namely creativity and enabling people to tell their story, what’s happening with documents and accelerating document productivity, and what’s happening associated with every single enterprise needing to engage with their customers digitally, when you add all of this up we think it’s over a $120 billion of an addressable market opportunity for Adobe.

Pandemic Was Inflection Point For Everything Being Digital

What the pandemic and the current health situation has done is that it has created yet another inflection point for everything being digital. What we will have to continue to monitor is what happens in the spending environment. But as it relates to the overall need for the kinds of solutions that Adobe provides as well as the importance of digital in the marketplace I think that’s going to be sustainable for decades. You’re not going to put the genie back in the bottle as it relates to engaging digitally and creating content digitally.

We believe that we’re in this third phase of what is happening in the enterprise. Traditionally, businesses first focused on automating the back office, and then they focused on automating the front office for knowledge workers. It’s absolutely clear that the biggest imperative that exists in the enterprise today is how do you engage with customers? This is a category that we call Customer Experience Management.

Customer Insight Is Key To Your Digital Transformation

If you’re an enterprise today and you’re thinking about digital transformation, what’s top of that stack in terms of where you have to invest is to make sure that you have insight into what your customers are doing. How are they engaging with you? What’s the profile? How do you deliver the personalized experience?

We really believe that what you’re seeing in the enterprise spend environment is that the companies that are focused on this next generation of delivering customer engagement, the customer experiences, and the insight associated with how to take the most advantage of that data, they’re going to be the secular winners moving forward.

IP blocking

AI-based systems can be used to block known malicious IP addresses and websites. Automated systems that use machine learning algorithms can quickly identify known malicious IP addresses and websites based on past data. These systems can then automatically block access to these addresses or sites, preventing users from accidentally accessing them. 

Spam filtering

We can use machine learning to develop better spam filters that are more effective at identifying and blocking unwanted emails. Spam email is one of the most common types of attacks organizations face today. To combat this, machine learning algorithms are often used to develop spam filters that are more effective at identifying and blocking unwanted emails. 

AI encryption

We can use AI-based systems to encrypt data so that it is unreadable by unauthorized users. Data encryption is one of the essential tools available for protecting information from being accessed by unauthorized individuals. We can use AI-based systems to encrypt data so that it is unreadable by anyone who does not have the proper key or password automatically. 

Browser protection

Smart browser-protection tools like WOT can enhance your cybersecurity by helping you to avoid malware, scams, viruses, and other online threats. These tools offer powerful anti-Phishing functions, popup blockers, real-time threat protection, and suspicious site detection, all within a powerful machine-learning construct—the perfect AI vehicle for keeping you safe online. 

Firewalls

We can use machine learning to develop better firewalls that are more effective at blocking malicious traffic while allowing legitimate traffic through firewalls. These are among the most important tools available for protecting networks from attack. However, traditional firewalls tend to be less effective at blocking malicious traffic while still allowing legitimate traffic. Machine learning-based firewalls can be trained to be more effective at distinguishing between different types of traffic and selectively blocking only the malicious traffic while still allowing the good traffic to pass through. 

Algorithms

We can use machine learning algorithms to analyze large volumes of data looking for patterns that could indicate a security breach. One of the most common ways cybercriminals gain access to sensitive information is through large-scale data breaches. To prevent this from happening, we can use machine learning algorithms to analyze large volumes of data looking for patterns that could indicate the presence of a security breach. 

AI Chatbots

We can use AI-based chatbots to intercept phishing attempts and other attacks. Phishing attacks often use email or other messages to lure victims into entering their sensitive information into a harmful website. To prevent this from happening, we can use AI-based chatbots to intercept these phishing attempts and notify the user before they have had a chance to enter any sensitive information. 

Machine Learning

We can use machine learning to develop better intrusion detection systems that are more effective at identifying and responding to attacks. Intrusion detection systems are designed to identify and respond to malicious activity on a network. However, traditional intrusion detection systems tend to have a high rate of false positives, leading to unnecessary alerts and wasted time and resources. We can train machine learning-based intrusion detection systems to be more effective at identifying and responding to actual attacks while reducing the number of false positives.

In Summary

AI is playing an increasingly important role in cybersecurity, with machine learning-based solutions being developed to address many of the challenges faced by organizations today. By leveraging the power of AI, organizations can improve their ability to block known threats, detect new attacks, and respond quickly and effectively to security breaches.

While it is still in its early developmental stages, AI technology has already shown great promise in cybersecurity. For example, AI-based systems can quickly identify and block known malicious IP addresses and websites by using machine learning algorithms. 

In addition, we can use machine learning to develop better spam filters that are more effective at identifying and blocking unwanted emails. Finally, we can use AI-based chatbots to intercept phishing attempts and other types of attacks.

Stephan Spencer, SEO expert, speaker, and author recently discussed the impact of AI on Google Search and SEO with James Schramko of SuperFastBusiness: (Listen to the full podcast below)

The Future of Google and SEO is AI

If you’re relying just on backlinks, then you aren’t recognizing that the future of Google and of SEO is AI, it’s artificial intelligence. What’s the best way, or the really the only way, to outsmart an AI? I would challenge that the only way to outsmart an AI is with another AI. So really, AI is the future.

AI and nanotechnology and all the cool technologies that are advancing, like VR, AR, etc., they’re happening faster and faster. And we need to be more nimble than we’ve ever been in order to keep up. So that’s kind of the game that we have to play.

SEO is Not Just About Machine Learning and AI

But right now, SEO is not just about having machine learning on your side to try and outsmart Google. It’s about having a search-engine-friendly website. It’s about identifying keywords that are relevant and popular and that are attainable for you in the Google search results. And it’s about achieving buzz and link equity by having people mention you and link to you. So those things still work, they’re still important to the Google algorithm. But on top of that, you’ve got to be willing to explore machine learning and be nimble about the future.

I’m personally excited about the future. I think it’s an amazing time to be alive. The kinds of advances that we’re about to experience in our lifetimes are going to be mind-blowing.

Bill McDermott, CEO, and President of ServiceNow says that only one in four digital transformation projects actually deliver positive ROI due to lack of integration:

Most Digital Transformation Projects Don’t Deliver

We have a situation on our hands where digital transformation, cloud computing, and business model innovation, are all converging at once. ServiceNow is the platform, of all the enterprise platforms, that really makes business work. One of the big lessons that business has right now is trillions have been poured into digital transformation yet only one in four projects actually deliver positive ROI. The reason for that is lack of integration.

Our system integrates with all the existing systems as well as all the collaborative tools in the enterprise. From day one, the customer gets it up and running swiftly because it’s in the cloud. They begin to derive value from it because you automate the way the work is done and ultimately, you’re now in a position to serve your customers the way they want to be served. It’s a speed game and ServiceNow is at the top of its game.

Companies Have To Create New Business Models

We’re an example. If you’re going to grow your company you’re going to take advantage of digital transformation. This is the only way out and it’s the only way forward. In the 20th Century companies put in big heavy on-premise systems. The issue is now they can’t, in a frictionless economy, immediately pivot those business models because they haven’t digitally transformed their business.

About 25 percent of the opportunity of businesses out there today over the next three years will come from white space places they are not in today. They have to create new business models. They have to think about new partnerships and new routes to market. Without the baseline of a platform like ServiceNow they’re not going to get there. 

That’s The Whole Point Of Digital Transformation

I am very optimistic that the economies of the world not only are going to recover but actually going to do very well this year because people are going to be investing in digital transformation. We have seen that does not cost jobs. On the contrary, it frees people up to do things like go after new markets, derive new ideas, and so forth, because the AI revolution is also on.

We have built-in machine learning and AI into our platform. So 80 percent of the soul-crushing work people don’t want to do is done by the Now platform. The 20 percent that involves a human immediately gets initiated through a workflow order from the Now platform. 

Business is really simple, and people are more productive and they’re doing things that can lead to growth and opportunity. That’s the whole point of digital transformation. Right now, companies are hunkered down with systems that are absolutely wearing them out. It’s time to make the bold move, pivot to ServiceNow, and let’s get in there and fix the job.

Fastest-Growing Pure-Play SASS Silicon Valley Company

If you look at our actual earnings results, they were stunning and obviously achieved beyond expectations performance across the board. We also followed that through in the guide. We’ll continue to be the fastest-growing pure-play SASS Silicon Valley company. We will continue to have the best margin profile of all of them. Obviously, we’re going to continue to gain market share in industries around the world, in geographies around the world, particularly in Europe and Asia Pacific, and Japan. 

We will also gain market share on personas. Lots of people are getting the memo now that ServiceNow obviously dominated the IT automation market but the same backbone platform has enabled us to change the employee experience, the customer experience. In these tough times with COVID we can write low-code onto our platform in minutes and roll out new applications to hundreds of thousands of people so companies can move super fast.

We keep the guide consistent with the revenue that we generated in 2020. If there’s an upside to that… fantastic. That’s what good companies should do. They should go beyond expectations when they can but we stand by the guide and we’re looking forward to having a great year. 

ServiceNow Was Born In The Cloud

The whole idea of ServiceNow is so different than SAP which was a company that needed to pivot to the cloud in 2010. We did that and that was very successful. ServiceNow was born in the cloud. It’s a very young company with tremendous growth opportunity on the organic front. Having said that, (we would be in interested in an acquisition) if you have a situation where there is a partner out there that has a substantial TAM, that can be highly complementary and synergistic with ServiceNow on the revenue side. 

It also would have to do great things for the customer, because we have a precious platform and we jealously protect the integration power of that platform. A lot of things would have to be right but I can tell you as responsible business people we always look at it. We don’t need it to make our goals but you always have to look at it. We do want to be the defining enterprise software company the 21st century. That’s our plan.

Brenda Harvey, General Manager of IBM Asia Pacific, discusses how the work at home acceleration caused by the pandemic has permanently broken down the barriers to digital transformation:

Cloud Driving Better Business Impact

The benefits coming from new personalized services, workflow automation, infusing AI to help drive this more personal experience, are actually driving better business impact. When we think about hybrid cloud which enables you to leverage all of your investments across your infrastructure we’re actually seeing two and a half times value than traditional models. We’re also seeing the benefits from regulatory cloud and capabilities that we’re putting into our platforms. We just announced a financial services cloud and we’ll do the same with insurance and healthcare.

We’ll take the costs out of the regulatory risk and compliance while providing more value from a business perspective. We’ve had a number of relationships across multiple industries including BNP Paribas, MUFG Bank, Adobe, across telecom with Vodafone Idea, Bharti Airtel, Verizon, and even Schlumberger and Ernst & Young. Companies are seeing the value of these platforms. In fact, in the study, 94% of the respondents said that by 2022 they would have a new business platform model that would continue to power their business.

Barriers To Digital Transformation Have Broken Down

We see continued growth of hybrid cloud and of cloud services after the pandemic. It’s touching every element of a company’s business processes from the inside out and the outside in. The inside out includes HR, finance, risk compliance, procurement, supply chain. Then the outside in, marketing, sales, customer engagement, and customer service. With marketing at marketing events, we saw a 3X response into our Think Digital than previous years because we could have more reach. So now marketing is taking into account a digital transformation of the clients’ needs.

Customer service and engagement are the number one priority of our clients. They are building and investing in the contact center to improve the experience and drive more value. This cloud platform will bring in new capabilities with 5G such as IoT (internet of things), blockchain, and of course quantum capabilities. We’ll see the technology advance while the cultural change is advancing too. The barriers have broken down now in digital transformation because of people working from home and the need to adopt faster.

Marc Benioff, CEO of Salesforce, discusses how we are not living in the past or the future, we are living in the present. He says that the present is a new digital world in an all digital world:

This Is About Helping Our Customers Thrive

We are, of course, in an unpredictable time. There’s never been greater uncertainty in the entire world because you have a global pandemic, you have a global economic crisis, you have a racial justice crisis, you have a global leadership crisis, and you have a global environmental crisis, and they are all happening simultaneously. There’s a lot of uncertainty in the world. That’s why we all really have to focus and get really clear on what we want right now and how we are going to succeed through these times.

This is a time that you can no longer do what you were doing six months ago. You have to do something totally new and if you can do something totally new you can have tremendous success. Salesforce is now an example of that success. We delivered a 29 percent growth quarter. It was amazing. That followed a 30 percent growth quarter. We also had record margins and we had record large deals. It was amazing how many very large transactions we were able to close during that time.

Ultimately, this is about helping our customers succeed and helping them thrive during this time. It was a 63 percent increase in seven-figure deals for our quarter. It is really because the largest most important companies in this world are all making dramatic changes and we’re there to help them connect with their customers in a whole new way.

We Are In A New Digital World… In An All Digital World

We are in a new digital world―in an ALL digital world. The past is gone. It’s not coming back. We are not in the future. We are in the present moment. This is a be here now moment. Everyone needs to realize that the past is gone. We are now in this new digital future and we need to rebuild our companies and organizations. Ultimately, we need to rebuild ourselves to be successful in this new digital future.

I just had a Board meeting last week. I had a Board member and they were talking about how great Zoom is and how we participated in this great IPO and successful it is. The Board members said that Zoom is really the future. I said, look, Zoom is not the future. Zoom is the present. This is our present reality. We are in a new world. This is our reality. We need to all make changes and we need to make them now because this is not going to shift anytime soon. If we’re going to succeed through this we need to realize that the past is gone.

We Can Create The Future That We Want

We are never going back to how it was. All of our employees are at home. Even in countries where we are open like Japan employees don’t want to even come in to the office because they have reskilled themselves. We have a whole reskilling engine called Trailhead.com. They use our tools. We have a tremendous salesforce automation tool that lets our employees sell to our customers remotely digitally. Our Sales Cloud is why we have tremendous sales, productivity, and success. Our Service Cloud is why we are having tremendous ability to service from anywhere and market from anywhere. The reason we’re the fastest growing top five software company in the world is because we use our own products.

This is just a minute in time where I say, wow, I didn’t see this coming. Nobody did. But now that we’re here we have to rebuild ourselves. At the same time we have to also augment for our customers what we can do. We are doing now contact tracing for thousands of companies. We run pandemic response management for 35 states. We didn’t have a pandemic response capability six months ago. Now we have to have it.

We have to be there for our customers to help them be successful whether they are public sector organizations or whether they are the world’s most important companies. This is a moment where if we all decide that we are all going to be successful and that the past is gone, we can create the future that we want.

Nigel Vaz, CEO of Publicis Sapient, discusses how the current pandemic has forced organizations to reimagine their businesses digitally. Nigel works closely with clients such as McDonald’s, Nationwide, and Unilever to deliver transformative experiences and business models:

Digitization Has Become Existential For Business

I think Digital has always been important for business. Now more than ever what’s becoming very clear is this has gone from being something that’s important to something that’s existential. How do you support customers to make orders entirely online when your stores are closed? How do you create mashups with other partners to be able to facilitate deliveries when your own deliveries don’t suffice? How do you try to create experiences online through self-service that minimize the impact of people calling your call centers? 

All of these things are things clients are facing on a regular basis. Most CEOs I’m in conversation with are acknowledging the fact that this has now got to be a priority, that they have to be ready more so than they’ve ever thought before.

3 Key Things Happening With the Transformation

There are three things happening here in terms of transformation. The first is the change in human behavior where I think there’s a recognizable shift now. We’re seeing significant accounts of over-70s, for example, ordering from retail and ramping that up. We’re seeing a big shift in institutions like schools and educational institutions, which historically had not thought about transformation as particularly applicable to them. 

We’re also seeing a shift in industries like leisure looking at creating virtual experiences since physical experiences are essentially restricted and people can’t use them. The human behavior shift is translating to big investments in technology and technology platforms that enable this. 

Businesses Being Reimagined In A World That Is Now Entirely Digital

Then lastly, new business models. There’s a real recognition that digitization and transformation are not doing what you used to do in the physical world. Digitizing that and translating that is essentially the journey of going from being a caterpillar to a butterfly. Real transformation. How do you reimagine yourself in the context of a world that now is entirely digital?

Customers are thinking very actively about how they actually create products and services that essentially create value for customers entirely digitally. There are plenty of examples in this from telemedicine and from the educational space with new courses coming online which can scale faster than traditional courses limited by a classroom and a professor.

The world’s two leading companies in the discovery & native advertising industry will remain fierce competitors in what still is a chaotic and unpredictable ad market.

“As part of the process we exchanged financial information with each other,” says Taboola Founder & CEO Adam Singolda in a blog post. “Based on the relative performance of the two companies, we decided the original deal does not make sense anymore. We could choose to pay the same price of 30% in equity + $250M, but our shareholders thought it’s too much for what we would get based on the relative contribution of the two companies. Nothing emotional, not about culture fit, just data.”

“Out of deep respect, we tried to do a deal that was equity only (but less equity), or equity and cash (but less cash) that matched Outbrain’s financial contribution to Taboola. We failed, and we called it off.”

Outbrain Co-Founder and CEO Yaron Galai expressed his own thoughts on the collapse of the merger:

“It is now public news that Outbrain’s planned merger with Taboola is heading to termination in the near future. This isn’t the outcome any of us anticipated for this process. We believed when entering this deal that there is great potential value to be had for our employees, our marketers and publisher partners, and our shareholders. However, this combination apparently was simply not meant to be. We worked hard to mix water and oil, but ultimately the companies proved to be too different to be mixed.” 

“During a very stormy year for the Outbrain team, due to both the pandemic and the cloud of the merger, Outbrain’s character as the #1 most trusted partner for the world’s best publishers has shone through very brightly. We’re excited to continue innovating and building the best native advertising products for publishers and marketers as an independent company for many years to come.”

Eric Schmidt, former CEO of Google, who is launching a new podcast today, discusses how AI will spawn a whole new batch of tech platform winners:

AI Will Create a Bunch Of New Platform Winners

Just 20 years ago the one really big player was Microsoft. Microsoft has now been joined by four other very large companies each of which is run cleverly but in a different way. They have different ways in which they win and they lose. We benefit from that brutal competition. Look at what you have in a mobile phone. The competition between Android and IOS and Apple phones and the Android ecosystem has brought a supercomputer into your pocket. That’s going to continue.

The reason it’ll be different in 20 years is because artificial intelligence will create a whole bunch of new platform winners. Remember that the way this works is the US establishes global platforms that everyone else uses. We are forgetting that it is US leadership at the platform level, whether it’s Google or Apple or what have you, that has brought us to this point where we have multi-trillion-dollar corporations that are leading the market.

Be Careful About Breaking Up The App Store Model

I don’t know enough about the Epic Games/Apple dispute because I left the board a decade ago. However, the important thing about the app stores is that they provide some level of security, branding, and protection for the user. In China, for example, Google does not have a single app store because of regulatory issues. So there has always been issues of is the app that you’re using certified and so forth.

I would be careful about breaking up the app store model as it does provide some security and protection. We can quibble about how they’re managed but the important thing is when you use an app store you can rely that what’s on it is represented to be what it really is. Just think of all those viruses that you are not getting as a result of the app store.

“The Qualtrics IPO is actually a win-win situation for both SAP and Qualtrics,” says SAP CEO Christian Klein. “When we are talking about Qualtrics let me first outline that Qualtrics was for sure one of the best acquisitions SAP ever did. They performed in the last 9 months above and beyond all the expectations we have set at the point of the acquisition. Now, three months back when I became the sole CEO of SAP Ryan Smith and I discussed a few options about how to move Qualtrics to the next level.”

“SAP’s acquisition of Qualtrics has been a great success and has outperformed our expectations with 2019 cloud growth in excess of 40 percent, demonstrating very strong performance in the current setup,” Klein stated. “As Ryan Smith, Zig Serafin, and I worked together, we decided that an IPO would provide the greatest opportunity for Qualtrics to grow the Experience Management category, serve its customers, explore its own acquisition strategy and continue building the best talent. SAP will remain Qualtrics’ largest and most important go-to-market and research and development (R&D) partner while giving Qualtrics greater independence to broaden its base by partnering and building out the entire experience management ecosystem.”

“When we launched the Experience Management category, our goal was always to help as many organizations as possible leverage the XM Platform as a system of action,” Qualtrics Founder Ryan Smith said. “SAP is an incredible partner with unprecedented global reach, and we couldn’t be more excited about continuing the partnership. This will allow us to continue building out the XM ecosystem across a broad array of partners.”

SAP agreed to acquire Qualtrics just four days before Qualtrics was to go public in 2018, recognizing the potential of bringing together experience and operational data (X+O) to help organizations take action. SAP currently owns 100 percent of Qualtrics shares. SAP will retain majority ownership of Qualtrics and has no intention of spinning off or otherwise divesting its majority ownership interest. Ryan Smith intends to be Qualtrics’ largest individual shareholder.

Christian Klein, CEO of SAP, discusses the reasons for their IPO and says that Qualtrics has been the best acquisition that SAP ever did:

Qualtrics IPO Is A Win-Win For SAP and Qualtrics

When we are talking about Qualtrics let me first outline that Qualtrics was for sure one of the best acquisitions SAP ever did. They performed in the last 9 months above and beyond all the expectations we have set at the point of the acquisition. Now, three months back when I became the sole CEO of SAP Ryan Smith and I discussed a few options about how to move Qualtrics to the next level. The partial IPO, we are both fully convinced, is actually a win-win situation for both SAP and Qualtrics. 

First, it will allow Qualtrics to focus on the non-SAP customer base in a high closed market. Second, despite the IPO, of course, SAP will remain fully committed to Experience Management (XM) and we will develop further use cases for our customers. We will also continue with the joint go-to-market. SAP is fully committed and will be in the long run highly committed to to Qualtrics and also will remain a majority shareholder of Qualtrics going forward.

IPO Allows Qualtrics To Go After non-SAP Customers

We kicked off already in the last 19 months, great use cases for our customers. We launched Human Experience Management (HXM) which helped both to accelerate the sales of Qualtrics but also our core application success factors. We did the same for commerce. In our product strategy, it actually plans to really expand experience management across our solution portfolio. 

Our employees are very excited about that because they see the benefits for our customers and this is something that won’t change with the IPO. This will allow Qualtrics more autonomy to also go after the market with non-SAP customers as this is a high quote segment.

Matthew Biboud-Lubeck, VP of Strategic Services at Amperity, discusses how their platform helps brands create a complete view of their customers in an interview on the B2B Growth podcast:

Helping Brands Create a Single View of Their Customers

We are a CDP (customer data platform) based in Seattle that is helping brands create a single view of their customers and to unlock personalized experiences from that data. If you look back to the founding of Amperity about three years ago our founders were canvassing the marketplace. What you saw was a marketplace using a lot of buzzwords but having a lot of trouble executing them. You heard about personalization, customer 360, and a 360 view of the customer. Marketers across major consumer brands were super frustrated.

They spent a fortune trying to cobble some view of their customer. They invested in technology to help them send better emails, to make their media more targeted, and to unveil better analytics. All of those tools that they have invested in talked about the notion of a single view of the customer because they fundamentally needed that to operate. The reality was that nobody was getting to the solution. We came in to say maybe there is a better way.

Machine Learning Helps Brands Get To Nirvana

There were two things that changed in the marketplace that we capitalized on. First of all, it was that cloud computing got a lot cheaper. It used to be that if you were a big brand and got hundreds of millions of customer interactions, it’s just a lot of data. Part of the reason that no one was able to create an easy solution to putting that all together was because it was cost prohibitive.

The second really interesting evolution in the market is that machine learning has become much more mature. What we found was that everyone in the marketplace was using machine learning to make that last mile to the marketer a little bit better. It was used to decide which products to show a customer or to decide which offer to show a customer or to create a customer care solution that’s automated. You go online and type toward a solution and some bot talks back to you. Nobody was using machine learning to point at the underlying consumer data to help make sense of it and bring it together.

We put together cloud computing that was scalable with better economics alongside a machine learning algorithm that we were pointing at the data to help make sense of it. We realized that what we had was a pretty scalable solution to help brands get to that nirvana of a single view of the customer. That’s how we were born. What’s interesting is that the customer data platform space is a little bit confusing. You have a lot of companies that started as something else that rebranded as a CDP. We were purpose-built from the ground up as a customer data platform designed to bring all of a brands data, reconcile that data to create a notion of identity on it and then to unleash that data back to the brand anywhere that they want to use that data.

>>> Listen to the full B2B Growth podcast here.

Adam Justis, Director of Marketing at Adobe Experience Cloud, discusses how AI and machine learning are enabling near real-time shopping personalization in an interview with theCUBE at Adobe Imagine 2019 in Las Vegas:

Role of AI in Offering a Personalized Shopping Experience is Core

You definitely have the data piece and then the content piece. I would also add how the complexity of all that has certainly exceeded the capacity to manage this in a singular sort of engagement with a customer, let alone at scale millions of times a day. So the role of artificial intelligence and machine learning now is so core. It’s sort of the gearbox that’s turning at the center of the data on one hand and the content and elements, the assets, the offers, on the other that allows for ultimately the coalescing of those things and then the delivery of an experience worth having.

That’s the component pieces that we’re seeing at play and Adobe’s motivation in going into that space. At Adobe when we announced our intent to acquire Magento, we were talking about how does Adobe facilitate or help every experience become shoppable and every moment personal? Really that was a claim we couldn’t make without the Magento piece. It is absolutely a hand in glove relationship especially as we’ve all evolved as consumers.

Advancements in AI Are Going From the Absurd to the Very Real

To imagine that we would be subscribing to socks or that we could one-click purchase just about anything, you need the technology that can keep pace with the expectations. That’s what it’s all about. So many of those experiences that Adobe is intent on enabling our customers to present culminate in a transaction of some sort. Magento is absolutely not only the icing on the cake but it’s also so integral. It’s becoming a fundamental or elemental part of what we’re trying to accomplish.

That (personalized experience) is one of the things that I absolutely love about customer experience management or CXM. In a way I kind of love the absurdity of it. When you think of the scale, to say something like we’re going to make every experience shoppable and every moment personal, to imagine that that’s possible is almost absurd. But when you introduce the advancements that we’re seeing in artificial intelligence and machine learning now it’s literally going from the absurd or the realm of science fiction into very real. That’s what Adobe is looking at.

Without AI Real-Time Personalization Would Not Be Possible

How can we literally take some sort of statement like we’re going to personalize experiences across the customer journey and we’re going to do it at scale and in real-time? Really, unless you’re considering how we’re going to meet the needs of the customer in the moment that they’re expressing that need then it’s really moot. It is absolutely artificial intelligence and machine learning that we’re seeing expressed now across the Adobe Experience Cloud that is making that happen in multiple ways. One of the ways would be simply by shortening that span between the latent genius that marketers are walking around in their heads and actual execution. How can we take some of the friction out of the workflows that allow them to translate their ideas into offers?

How do we shorten the space between a signal that we get, say in behavioral data that we see show up either in an app or on a website, and then churn through all of the possibilities of what we could present, apply algorithms to determine what is the next best offer and next best experience? Then how do we present that in a way that actually feels if not real-time pretty close to it? That would not be possible without artificial intelligence. At Adobe we do that through a product called Adobe Sensei.