Hi Hendrik, welcome to AiThority.com’s Predictions Series. Please tell us about the evolution and ever-changing role of Artificial Intelligence (AI) capabilities in sales enablement.

I think Sales enablement companies are taking AI to the next level already. 

As buyers get smarter with more information at their fingertips, sellers will need to leverage AI to keep up. 2023 was undoubtedly the year in which AI entered the mainstream consciousness, but the nuances and the advantages that AI can offer in a business environment, are still being worked out.

To maximize the almost unlimited possibilities that AI can offer, sellers will need to harness it in their sales meetings to drive better buyer interactions, stay one step ahead and be ready to add meaningful value to the conversation.

Whether it’s using AI to instantaneously surface the most compelling pitch deck, talk track, or playbook, AI will enable sellers to show up as trusted advisors, earning buyer confidence and becoming indispensable to the customer journey. In addition to sales meetings, AI will also be leveraged to augment the role of the internal sales coach, making sales development programs smarter and more scalable. The latest innovations mean that AI can provide actionable insights on seller skills and behaviors, helping define a baseline for sales readiness, and deliver targeted support to the reps who need it most. And if you’re not integrating AI into your sales strategy, you will be opening yourself up to a brief creep from your competitors.

With AI, can we finally expect alignment between Sales and Marketing functions? 

Yes, we can finally see a better alignment between Sales and Marketing using AI.

For years businesses have tried and failed [epically] to align sales and marketing teams. In a recent survey, approximately 70% of organizations said their sales-marketing alignment was not very good, leading to frustration and finger-pointing. However, new enablement platforms coupled with AI will finally make this a reality. When sales and marketing teams can better align, they can sustain and nurture relationships with buyers.

Alignment will also ensure maximized revenue and growth opportunities for the business.

Bringing sales and marketing teams together will allow them to collaborate on key business goals and see how each department impacts the other.

Customers will be delighted when their needs are anticipated, understood, and managed in real time.

With alignment, there will be more rapid deal cycles as customers are engaged and ready to buy.

What avatar would the Customer Relationship Management (CRM) solutions take in 2024?

According to me, CRMs would evolve into Sales Enablement Platforms (SEPs).

Customer Relationship Management (CRM) and Sales Enablement Platforms (SEP) are both crucial tools in the modern sales and marketing landscape, but they serve distinct functions. While CRM systems were about managing customer relationships and data, the reality is they have become more about customer record management. Meanwhile, sales enablement platforms are about empowering sales teams to engage more effectively with those customers.

In today’s world, businesses need a system of engagement to complement their system of record, and this has made Sales Enablement technology a must-have. Put simply, it is where the relationships happen. CRM systems are designed to manage interactions with current and potential customers, tracking the history of customer engagements, sales opportunities, and service requests. They are invaluable for maintaining detailed records of customers and long-term relationship building.

On the other hand, SEPs focus on equipping revenue enablement teams with the tools, content, and information needed to sell more effectively. These platforms provide resources like sales training materials, content management, and analytics tools to optimize the sales process.

It’s only a matter of time until SEPs outweigh CRMs in importance and additive value.

Recommended AI ML Article: State of Implementation of Generative AI (Gen AI) in Marketing

Thank you, Hendrik! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

• About Hendrik Isebaert
• About Showpad

About Hendrik Isebaert

Hendrik Isebaert is Showpad’s Chief Executive Officer. After joining the organization in 2016, Hendrik embarked on an extensive business immersion, working in leadership positions across Showpad’s dual headquarters in the U.S. and Belgium.

Beginning his Showpad career as Chief of Staff, Hendrik was subsequently promoted to the role of Managing Director for Europe, Middle East and Africa, and latterly to Senior Vice President of Revenue globally.

About Showpad

Showpad is a leading sales enablement platform.

The post AiThority Interview with Hendrik Isebaert, CEO at Showpad appeared first on AiThority.

 Adaptive streaming technology platform SeenThis and Audi have announced the results of their first digital campaign together, with SeenThis’s innovative adaptive streaming technology used in a digital display and VOD campaign to promote Audi’s Q4 Sportback e-tron.

Thanks to SeenThis’s cutting-edge technology, there were no file-size restrictions on the creatives uploaded, with all assets optimized and the quality of the video stream always adapted for the user’s bandwidth – to provide the best possible experience with minimum data consumption.

The campaign launched in France on September 5th and ran until October 8th across three IAB formats: 300×250, 300×600, and 729×90. According to Audi’s media agency Re-Mind PHD France, this led to a doubling of the click-through rate (CTR), from 0.11% to 0.22% compared to previous campaigns. Streamed with SeenThis technology, the campaign also transferred an estimated 33% less data compared to delivering the same quality creative using conventional technology. This resulted in an estimated 10% avoided CO2 emissions from creative delivery.

Jesper Benon, CEO at SeenThis, comments: “The campaign marks the first time that SeenThis has worked alongside Audi. It was great to see both the media and CO2 performances of the campaign exceeding expectations. We’re all about combining performance with sustainability and high quality – optimizing with lightning-fast ad-loading that grabs users’ attention and leads to more efficient use of resources.”

Stéphanie Cantau, Media Manager at Audi France comments: “We were ambitious for our campaign for Audi Q4 Sportback e-tron, with its unique design which concentrates the best of Audi driving, offering unique sensations on the road. And, so we were thrilled that this campaign reflected the brand’s passion for innovation and progress, while also reducing carbon emissions through the latest technology.”

The teams worked together with Re-Mind PHD France to drive optimal results, with Ludovic d’Aubert, Associated Director at Re-Mind PHD France adding: “We wanted to highlight the Q4 e-tron model in a very premium way, with clear differentiation and impact. The majority of the budget – 70% – was allocated to performance, while monitored KPIs included CPC, CTR, CPV, volumes of clicks and visits, time spent on the landing page, and conversions.

Across the board, the work exceeded all our expectations.”

SeenThis launched an Emissions Dashboard earlier this year to enable advertisers to track both campaign performance and carbon emissions, with emission reports available at the campaign, creative, and agency levels. Its investigations into the relationship between data wastage and CO2 emissions have also led to the publishing of a whitepaper. SeenThis technology is compatible with all major ad servers, publisher networks, and third-party providers. 

Since 2017, Swedish tech company SeenThis has been evolving screen experiences for everyone, everywhere.

With its groundbreaking adaptive streaming technology, SeenThis is transforming the distribution and climate impact of digital content compared to traditional technology. With billions of streams served for 1000+ brands in 40+ countries, the company is on a journey to reshape the internet – for good. Working across seven offices globally, SeenThis employees are obsessed with creating a truly high-speed and energy-efficient Internet. 

[To share your insights with us, please write to sghosh@martechseries.com]

The post SeenThis and Audi Double CTR and Cut Emissions in Inaugural Partnership appeared first on AiThority.

More industry veterans move to in-game advertising as the channel proves significant growth opportunity

Frameplay, the award-winning, global intrinsic in-game advertising leader, has appointed two new chief officers to its executive team as it prepares for continued strategic growth: Sandy Shanman as Chief Operating Officer and Vishal Arora as Chief Technology Officer. The hiring of these two martech veterans signals the industry’s commitment to gaming as an advertising channel, as more brands and marketers experience the value of in-game advertising and gaming strategies become a new standard in omnichannel campaigns.

For over 20 years, Shanman has led emerging revenues at the crossroads of media and technology, from early stage to exit. Most recently, he scaled and diversified revenue at Skai (FKA Kenshoo), ushering in the era of retail media. Shanman was previously CRO at Samba TV, one of the inaugural companies to drive media dollars into the CTV sector, and went on to lead revenue and operations at ChefsFeed (acquired by Tastemade), one of the first influencer media platforms.

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“I’ve witnessed transformation across the digital media landscape for over two decades, and I am convinced that intrinsic in-game advertising is poised to be the next tectonic shift–on the order of magnitude of CTV,” said Shanman. “Microsoft, Netflix, and numerous streaming services are expanding aggressively in the sector. The most viewable and highest performing placements within games are intrinsic, and Frameplay’s technology and measurement capabilities enable brands to capitalize on this engaging medium at scale.”

As CTO, Arora brings over 20 years of experience managing ground breaking technology teams to Frameplay. Arora joins Frameplay from Google, where he led the Ad Platform Services Engineering team through a transformation that involved a rewrite of their ads billing systems, which process the majority of Google’s revenue. Before that, Arora helped launch and scale the current Google Ads UI, and, as CTO at RxSense, helped build and bring a new enterprise platform to market.

“Gaming is a mass-reach medium and Frameplay’s ad serving technology supports high-quality, viewable intrinsic ad placements across multiple devices in milliseconds, without infringing on game performance,” said Arora. “The technology fueling intrinsic in-game advertising is innovative, seamless, and effective. Frameplay is reframing how the advertising industry leverages gaming as part of their brand spend. I look forward to being a part of the Frameplay team as we continue to raise the bar for in-game advertising.”

With a growing global player count of over three billion, in-game advertising has gained significant momentum among brands and game studios in the last five years. As a result, multiple major holding companies have established gaming branches, and brands have developed dedicated gaming strategies with increased spending in the channel.

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“Having veterans in the martech and adtech worlds join Frameplay speaks volumes to the industry’s commitment to in-game advertising and that major players in the industry understand the opportunities it presents for brands,” said Jonathon Troughton, CEO of Frameplay. “In-game advertising, and the entire gaming industry, has been growing and evolving rapidly. Sandy and Vishal’s combined leadership will be instrumental to our future, and will help us continue to set the standard for intrinsic in-game advertising.”

These executive hires are not only a milestone for Frameplay, but also the in-game advertising industry. The demand for in-game advertising continues to grow as the technology fuels more innovation and opportunities for brands, developers, and players.

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[To share your insights with us, please write to sghosh@martechseries.com]

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As we approach 2024, the popularity of generative AI will ultimately impact every sector of the economy. It is important to identify which sectors are most primed for the early adoption of AI and to consider the extent to which AI will fundamentally and rapidly transform these sectors.

Marketing is one of the sectors ripe to gain from artificial intelligence.

Why is that?

Marketing activities, such as understanding customer needs and monitoring their behaviors to provide them with the right offer at the right time across channels, can be significantly enhanced by AI.

With that in mind let’s focus on how AI will be leveraged to augment and assist future marketers in accomplishing their tasks with increased speed, efficiency, and scalability. This will be achieved by utilizing AI with human interaction, oversight, and approval processes.

With global spending on AI to reach nearly $200 Billion by 2025, here’s a look at key trends on the pivotal role of AI in marketing for 2024:

AI providers will help augment work. 

Every vendor will highlight how their products utilize AI and can benefit brands. We will see how their product’s version of agents, bots, and features help augment daily tasks.

Major technology corporations (Google, Facebook, Amazon, Apple, and Microsoft) will maintain their aggressive approach toward investments and the introduction of new products and capabilities.

Riding on the Generative AI Hype, CDP Needs a New Definition in 2024

We can expect to see an influx of emerging start-ups that specialize in developing artificial intelligence solutions tailored to the specific needs of their clients. These start-ups leverage the existing platforms offered by the larger technology companies, enabling them to innovate and expand rapidly.

Marketing technology providers will also be aggressive in releasing the next wave of native features and capabilities, aiming to enhance the overall user experience for marketers.

Adoption will go beyond the hype. 

Organizations will start to effectively leverage AI beyond the initial hype of ChatGPT. AI will enhance work processes and decision-making across all areas of a business, ranging from customer-facing operations to administrative tasks.

With so much to choose from, organizations will start small with AI implementation with specific use cases and areas where AI can provide the most value.

Additionally, to address the talent gap and governance, organizations will invest time and effort into developing a strong AI culture within the organization, promoting a mindset that embraces AI technology by providing training and resources to employees.

Technology solution providers will adapt and innovate their services to help organizations maximize the potential of emerging AI products.

The crucial factor for companies will be to carefully assess whether to develop in-house solutions, procure from external sources, or outsource the required expertise. The expertise and experience of tech solution providers will prove invaluable in expediting the implementation process with their frameworks and tools to build a foundation to expand on.

Further, tech providers will bring domain expertise and data assets that will supplement enterprise data. This will help brands leap forward from legacy machine-learning models to purpose-built large knowledge models (LKMs) that use the power of neural nets large-language models (LLMs).

One of the key challenges will be selecting the appropriate AI provider or components and seamlessly integrating them into the overall solution. With a multitude of options available, there will likely be a wide-ranging marketplace with countless possibilities.

What will AI enable, and why consider it for marketing?

AI will solve the classic marketer’s problem of who, what, and when — day-to-day marketers’ functions that are time-consuming and inefficient.

Let’s look at three key areas:

1. Improve Customer Experience and Customer Satisfaction

Many brands are keenly focused on delivering a better customer experience, but the reality is that it is hard and time-consuming to deliver the right message at the right time at scale across channels.

Artificial intelligence’s exceptional abilities in data analysis and pattern recognition will revolutionize personalized marketing. By employing AI, brands will be able to analyze consumer behavior, preferences, and purchase history, allowing for tailored marketing strategies for each individual. This level of hyper-personalization will go beyond mere product recommendations and extend to personalized advertising, content, and even customer service interactions.

2. Employee Productivity

In the design process, AI will help create content like text, video, and images quickly with text-to-image capabilities. Further, marketing tools will have native features to create variants and speed up A/B testing.  AI assistants will complement, support, take the guesswork out, and provide suggested paths to utilize.

3. Operational Efficiencies

AI will streamline various marketing processes, from automated customer segmentation to predictive analytics for demand forecasting. This will lead to not only more targeted marketing campaigns but also substantial cost savings and improved ROI. Marketing assistants with chat-type natural language prompting will be everywhere to support marketers and make available their time for more advanced tasks.

In conclusion, the future of marketing is undoubtedly intertwined with AI.

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As technology advances, AI will continue to play a pivotal role in shaping marketing strategies and campaigns.  It will automate repetitive tasks, freeing up marketers’ time to focus on strategic initiatives, and ultimately boosting efficiency and productivity. The time to get started on marketing with AI is now. Prepare yourself and be ready for exciting times ahead.

[To share your insights with us, please write to sghosh@martechseries.com]

The post 3 Key Trends for AI and Marketing in 2024 appeared first on AiThority.

The world of customer data is rapidly changing, and companies are responding with diverse strategies to stay ahead in this dynamic environment. At our recent Amplify summit, industry leaders and professionals from iconic global brands like Deloitte, Patagonia, Taco Bell and more converged to explore the evolving landscape of data-driven marketing and the profound impact of first-party data.

Under the overarching theme of “Together We’re Electric,” the event explored critical facets of using customer data for strategic advantage, with a focus on the future of paid media, best practices for Customer Data Platforms (CDPs),  and the transformative power of establishing a unified data foundation with Amperity.

Let’s dive in.

The Right Tools for a Shifting Landscape in Data-Driven Marketing

Amperity CEO Barry Padgett kicked off the event with an analogy: a CDP is like an electrical outlet, with all the circuitry behind the wall making it work and the appliances that get plugged in making things happen. The data foundation is behind the wall, and all the marketing and analytics tools get power from the foundation.

He emphasized the importance of both halves of the customer data equation — what goes on behind the outlet and what gets plugged in — working in harmony to create a seamless flow, from data intake and unification to insights and activation to revenue.

“Customer data should always be two things: reliable and repeatable. Results are only as good as the data you feed it. We must get the data right,” he says. This collaborative approach is even more important at a time of heightened external pressures like regulatory compliance, technical evolution, and the demands of knowledgeable and savvy customers.

Next was the keynote unveiling of Amperity for Paid Media, a new solution addressing the challenges to the traditional methods of digital advertising due to the continuing deprecation of third-party data and evolving content and privacy regulations. Amperity CTO and Co-Founder Derek Slager laid out a customer data strategy focused on using unified first-party data to power paid media and be much more effective than a third-party-forward approach.

This isn’t a future state: Amperity is already sending more than 12 billion profiles a day to the majority of top media partners, and brands adopting a first-party-first strategy have seen great results, including match rates as high as 85 percent on key channels, improved return on ad spend (ROAS) by up to 5x, and up to 90 percent faster activation time for new campaigns. The keynote summed it up as “better data, better results.”

First-Party Paid Media Strategy in Action

Several sessions unpacked the future of paid media, making it clear that this moment in digital advertising is both evolutionary and revolutionary. Things are changing, and they’re not going back.

With third-party-reliant systems growing obsolete, it becomes critical to base your approach on first-party data to navigate the changing ecosystem. We heard from Wyndham Hotels & Resorts, Citizen Watch, and Taco Bell that they’re working with Amperity to unify and use their owned data for advertising, seeing tremendous results.

They shared their experiences with change management when transitioning to a unified customer profile approach. They also discussed how adapting their paid media strategy pushed them to think about other ways to use customer data in different settings, emphasizing the critical role of a unified customer foundation in making any of it possible.

Mike Shiwdin, VP of Digital Optimisation, MarTech, Guest Intelligence and Engagement Strategy at Wyndham Hotels and Resorts, shares, “Anticipating your guests’ needs and acting on them is the core of hospitality. First-party data allows us to truly understand who those customers are and what they want and need across our 20-plus brands globally. So that was really where we first started: How do we better understand who is a budget hotel customer, who is in a registry collection, who’s spending $700 a night at an all-inclusive resort?

“From a paid media perspective, we started with suppression. Without first-party data, we had a one-size-fits-all approach. So that was the clear proof of concept to drive value internally to build momentum in the investment. Now as we’re three years into it, we’re starting to build a robust retargeting effort. And we’re seeing material results. We’re starting to get more of a sense of how we expand out across paid media,” he continues.

“Once we saw the value of paid media at Wyndham, we slowly started to mature into the realization of how first-party data isn’t just about the next transaction. And, we started to see the real value of first-party data and a CDP with Amperity. The next transaction — the value of that is just incremental touchpoints to build a stronger relationship with your guests.”

CDP Best Practices: Scoping, ROI and Use Cases

During the summit, we also dug into the different aspects of using a CDP, including hearing from SPARC Group about building a multi-brand strategy with a unified data foundation and exploring the three pillars of ROI strategy at Vail Resorts.

We had the privilege of learning about how CPG company Reckitt makes a CDP work at a global scale. Bastian Parizot, Global Head of Tech and Digital at Reckitt emphasizes, “First-party strategy for us is about how we take control of that ‘seed’ that helps us do better at media targeting, to be more relevant in advertising and start building a direct relationship.”

Sessions with Vince and Citizen Watch walked through a variety of specific use cases for marketing and analytics, with a focus on tying together the customer experience across all touchpoints. For example, Rob Harvath, VP of Consumer Insights and Data Management at Citizen Watch, says, “The power of a CDP like Amperity is that it has made my life a whole lot easier, but it’s also made us a whole lot smarter about who our customers are.

“Amperity has helped me tell the company and our sales team who our customers are, all the way down to the individual model of watch they bought. So when you take into account all of our brands, all of the collections within those brands, all the way down to the individual model, guess what? Our data now is structured so that I can answer the question, who’s the customer for this particular watch with these attributes.”

We also heard from Taco Bell collaborating with AWS on how it went from having no customer data to operating seamlessly between digital and in-person channels, using data to understand customer preferences and creating personal experiences that build loyalty. Dane Mathews, Chief Digital Officer at Taco Bell, emphasizes, “Loyalty is transforming customer expectations, retail experiences, and the QSR business model.”

From Unified Data to The Downfall of DMPs

The speakers emphasized that the success of their marketing strategies hinges on having a unified data foundation as the bedrock. They shared their experience of how important it is to be able to feed accurate data to a whole range of tools for various use cases like omnichannel, multi-databases, and real-time profile API.

On the culture and change management side, speakers agreed that each organization’s initial use cases and CDP rollout plan should be tailored to their specific needs. But regardless of what they’re trying, they need to be able to see ROI quickly.

There was also a session from David Chan, Managing Director at Deloitte Digital discussing the future of customer data. He explained why brands need to make the move from Data Management Platforms (DMP), which were previously popular but dependent on third-party data and thus increasingly less viable. He recommended that brands move to a CDP, which maximizes first-party data, and explained how clean-room technology is vital to making that move happen.

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Strategies and Tactics for Reshaping Customer Engagement

Some of the sessions asked, what does it take to put together a data foundation that can turn customer data into business value?

Patagonia Manager, Customer Insights and Analytics, Dan Sundaram, shares, “[With Amperity] we can illuminate touchpoints across the brand that we’ve never been able to see or understand. And that lets us talk to people in a much more relevant, less intrusive way, which in a world of personalization is the key to valuable customer relationships.”

Databricks also joined Amperity on the stage to discuss the concept of a ‘composable’ CDP, which involves solving CDP-related challenges using individual point solutions, also known as a modern data stack. One of the takeaways was that the point solutions within a composable CDP do not create unified customer profiles — which is itself a highly specialized technical problem that needs to be solved to make the other points work more effectively. (And, incidentally, this is the problem Amperity was built to solve.)

The Future of Data-Driven Marketing is ‘Electric’

We’re on the cusp of a remarkable transformation in the realm of customer data. The Amplify Summit offered a glimpse into the future where the power of unified, reliable data is harnessed to drive unprecedented levels of innovation, engagement, and growth. The future of data-driven marketing is here — and the possibilities are “electrifying”.

[To share your insights with us, please write to sghosh@martechseries.com]

The post The Future of Data-Driven Marketing appeared first on AiThority.

Tealium is recognized for its demonstrated technical proficiency and proven customer success in the advertising and marketing industry

Tealium announced that it has achieved the Amazon Web Services (AWS) Advertising and Marketing Competency, which marks its fifth competency with AWS. In addition to the Advertising and Marketing Competency, Tealium has earned competencies in Retail, Data & Analytics, Travel and Hospitality, and Financial Services.

Achieving the AWS Advertising and Marketing Technology Competency recognizes Tealium for its expertise in providing customers with a software solution that empowers advertisers and marketers to reinvent workloads through their CDP with machine learning, tag management, an API hub and data management solutions that make customer data more valuable, actionable, privacy-compliant, and secure.

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As advertisers and marketers look to leverage the cloud to innovate and achieve digital transformation, they are increasingly in need of partners with services and solutions that are purpose-built to meet their needs. AWS Advertising and Marketing Technology Competency Partners provide these customers – including advertising agencies, marketers, publishers, advertising and marketing technology providers, and analytics service providers – with AWS-validated solutions and services, helping to accelerate their transformation.

Achieving the AWS Advertising and Marketing Technology Competency differentiates Tealium in the AWS Partner Network (APN) with demonstrated technical proficiency and proven customer success in running cloud solutions on AWS for the advertising and marketing industry.

To achieve the AWS Advertising and Marketing Technology Competency, AWS Partners must undergo a rigorous technical validation by AWS solution architects and have verified customer references.

“We are delighted to achieve our fifth AWS competency in the Marketing and Advertising sector, which faces substantial challenges due to evolving privacy regulations and shifting data dynamics,” said Matt Gray, Head of Global Partnerships at Tealium. “In today’s environment, it is imperative for brands to adapt their customer engagement strategies. Through the powerful synergy of Tealium’s best-in-class CDP and AWS services, brands can expedite their digital transformation initiatives while fostering standardized, unified, and fortified customer data strategies.”

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Jysk Fynske Medier (JFM), one of the largest Danish news and publishing groups, recently worked with Tealium to create a more holistic customer view and enhance the customer experience.

“The impact of regulatory changes around third-party data is a major challenge particularly when looking at the amount of websites and publishing assets under the JFM portfolio,” said Dennis Vesti Brorsen, Head of Data & Intelligence, JFM. “Tealium AudienceStream and iQ Tag Management really was the Swiss army knife of data management systems for us. It’s flexible and applicable to various use cases, which often came up spontaneously. Its capability of providing us with a holistic customer view that enabled an optimized personalization and targeting process, allows us to not only survive, but thrive, in the marketing jungle.”

AWS is enabling scalable, flexible, and cost-effective solutions from startups to global enterprises. To support the seamless integration and deployment of these solutions, the AWS Competency Program helps customers identify validated AWS Partner solutions and services for specific industry use cases. Explore the AWS Partner solutions and/or services offered in AWS Data Exchange, AWS Marketplace, or APN Partners, including Tealium.

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[To share your insights with us, please write to sghosh@martechseries.com]

The post Tealium Achieves the AWS Advertising and Marketing Technology Competency appeared first on AiThority.

Authenticity in advertising, especially in the age of advanced social media techniques and the Metaverse, has become extremely challenging. Where consumer trust and public skepticism are at an all-time low, brands are in danger of creating an existential future for themselves, especially when inauthentic and lowest-common-denominator messaging remains the most significant part of their strategies.

Not surprisingly, an Ipsos Veracity Index from 2022, which surveyed UK adults’ trust in various professions in Britain, found that advertising executives were amongst the five least-trusted professionals, alongside politicians and government ministers. But, perhaps shockingly, journalists have also joined their ranks, highlighting the challenge of the media to gain public trust.

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So, with so many advertisers getting their strategies wrong, how can companies and media providers authentically interact with consumers that resonate with them the most?

Delivering exactly what consumers want

There is a belief that for every consumer, there are 100 pieces of content produced. Therefore, to stay competitive, brands need to promote their content in a way that sets them apart from competitors and strengthens relationships with their consumers. Ultimately, companies must offer the desired content and user experiences that meet their expectations to encourage people to visit their channels more frequently and stay longer.

Successful content marketing delivers what consumers seek: relevant content, engagement, dynamic search features, and seamless interfaces, all contributing to efficient research and user experiences. As a result, brands can achieve their goals of increased website traffic, a growing consumer base, more followers, and higher revenue.

It is also important for brands to identify the channels and methods through which their target audience accesses information.

For example, although social media platforms are excellent for distributing content, their ever-changing algorithms and user agreements make them unstable platforms for building a content marketing strategy.

Staying true to your values

Brands should also focus on following their values and walking the walk. Unfortunately, too often companies rush to monetize content from social events and awareness days to increase publicity and profit. One of the most prominent examples in history is the Black Lives Matter movement in 2020, where companies were too quick to release statements of support via social media posts and TV advertising spots. However, little did they expect to be put under a microscope by consumers, with many brands trending for all the wrong reasons and going in the opposite direction of unification and solidarity for the BLM movement.

This highlights an important lesson for brands – not aligning your values and actions with marketing and advertising strategies is the direct route to disengaging your customers and creating a negative image. Seeing how these mistakes can damage the reputation of even well-established businesses such as McDonald’s and P&G, smaller brands should spend more time researching their audiences and rethinking their strategies if they can’t prove they are aligned with company values.

This is particularly true for younger generations, who are more in tune with expressing their opinions and advocating for their beliefs. The “cancel culture” is real, especially amongst Gen Zs. Customers are responding better to ads that showcase company values and a sense of humor – perhaps the most famous example is Oatly with their “wordiest, stupidest billboard” campaign in 2021 which went to great lengths to tell its audience all they need to know about the brand.

Seeking creative ways to deliver content

As we’ve seen, it’s essential for brands to stay authentic, find their voice, and tailor their content. Sponsorship of liveblogs is a way in which brands can better connect and engage with different types of audiences and make sure their content gets in front of the right consumers.

Liveblogs enable bloggers, publishers, media houses, businesses, and more to create immersive live content stories and better engage with audiences. The technology can cover and report on almost anything – from natural disasters, sporting events, and live elections to own blogs detailing the latest fashion or cooking trends. By sponsoring liveblogs covering topics related to their brand, like the Minute Maid Orange Juice sponsorship of a Good Morning Liveblog for example, brands can associate their names with valuable content that also feels authentic. Also with the increase in ad-blocking technology, live blogs are emerging as a more effective platform for brands to advertise.

Our research shows that consumers relate to short, snappy, digestible, and relevant content. Brand ads can also be displayed at different points within liveblogs, allowing more ads to be integrated within one story without the advertising overwhelming the consumer like it sometimes does on articles.

Sponsoring liveblogs or integrating ads within them can be easier for smaller brands, with key monetization opportunities available to help turbocharge their revenue streams, enabling them to compete with larger brands – in an authentic, tasteful, and noninvasive way.

The road to ethical advertising strategies is proving to be much trickier than expected by many companies. Long gone are the days of blanket messaging and utilizing broader channels – how customers consume media has changed, dramatically impacting their values and beliefs. For companies to stand out, they must take a long hard look at their values and see whether their internal operations match their advertising and marketing strategies. Balancing nurture content focusing on brand values and user needs and revenue-driving content will help influence the brand’s authenticity and drive consumer engagement and sales.

[To share your insights with us, please write to sghosh@martechseries.com]

The post Building Brand Loyalty with Authentic Advertising appeared first on AiThority.

Artificial Intelligence (AI) has become a common buzzword in the business sphere, with everyone eager to leverage the potential that AI holds. Following the development of large language models (LLMs) like ChatGPT and other AI-based technologies such as Microsoft Copilot, business leaders have been quick to ask the right questions about adopting the technology into their everyday operations. One question that I now often hear prospective clients ask is “How can AI transform the way we interact with and understand our customers?”.

Enter CRM. The CRM landscape is rapidly evolving thanks to AI and machine learning. Companies like Salesforce and Microsoft are already integrating generative AI into their CRM Customer Service platforms to act as intelligent sales reps. These AI tools recognize customer needs and interests, recommend optimal products and services, and answer complex customer queries in real-time. AI looks poised to transform CRM, sales, and marketing in years to come.

But, how?

And, how can companies stay AI-ready?

Delivering customized experiences

One of the greatest advantages of an effective CRM is the ability to improve customer relationships. By providing personalized experiences and catering to the specific needs of customers, businesses can create a loyal customer base. With this, businesses can track and analyze customer interactions to identify their preferences, interests, and behavior.

And now with the powers of AI, businesses can deliver a new level of customization. Integrating AI in CRM systems delivers more tailored recommendations, content, and experiences – all made possible by machine learning algorithms that can analyze huge sets of highly valuable data. By analyzing purchase history, website activity, social media, and survey feedback, businesses can benefit from detailed customer profiles. With this, companies can segment audiences, predict behaviors, generate more customized marketing content, and deliver personalized services that meet their unique needs.

AI is set to transform CRM systems by providing excellent customer-focused experiences and developing stronger relationships, which will ultimately attract loyal customers who will return for repeat business and even recommend their products or services to others.

Driving better decision-making

AI opens new doors for data-driven insights and decision-making. With the power to filter customer data to spot trends, patterns, and correlations, AI can analyze data at a speed that humans simply cannot. This drives incredibly accurate forecasts and modeling of future behaviors, needs, and pain points.

By identifying these trends, CRM systems will become more and more advanced. Sales teams can see the full picture with access to this analysis, which can inform marketing and sales strategies and enable better decision-making to achieve greater revenue growth.

Boosting efficiency via automation

Automation is something that many companies look to achieve. After all, it improves workflows, reduces costs, and mitigates human error and delays. This is exactly where AI can support CRM systems, by streamlining operations and increasing efficiencies, freeing up valuable time for staff to focus on more pressing tasks and campaigns.

Chatbots and virtual agents can automate customer services significantly when done well – this is important. When tools have advanced natural language capabilities in place, bots can understand context and intent, providing increasingly human-like interactions. This is currently a work in progress, but tools that leverage AI are getting better and better by the second.

AI can also support by automating routine tasks such as data entry and customer follow-ups. It can help companies stay on top of customer conversations across multiple channels and touchpoints. And, with the ability to auto-categorize customer communications, flag complaints, and urgent matters, and route them to the right department, AI has huge benefits for companies’ CRM customer service systems.

Staying AI-ready

Amidst the excitement, it’s crucial to recognize that AI works with the tools and information that it is given.

Therefore, it is essential that businesses lay the right foundations before jumping on the AI bandwagon. Currently, many organizations lack the essential technological and process frameworks that are the prerequisite for successful AI integration.

Companies with robust CRM systems already in place, and a commitment to basing decisions on data, are well-positioned to begin implementing artificial intelligence into their everyday operations. Over the next few years, these organizations can be expected to begin integrating AI capabilities into their already existing CRM platforms, which would enable more personalized and automated interactions, taking their customer experience to the next level.

Businesses that have fragmented customer data across multiple sources, on the other hand, are predicted to face more obstacles in their AI journey. Consolidated and organized customer information is a standard prerequisite for unleashing the potential for AI. In this instance, compiling dispersed data from various legacy systems and spreadsheets into a unified database needs to be prioritized before the organization can begin to fully implement AI across all its systems.

Of course, AI is constantly evolving, and even when systems are ready, there are challenges.

Once models are trained, there will be a need for ongoing supervision, maintenance, and adjustments, meaning companies will need to budget for ongoing AI support staff to ensure systems are working effectively.

Companies will also need to be mindful of bias within models. Avoiding bias will be critical in ensuring companies prevent discriminating against their customers and reflect their ethics. This is key to establishing relationships with customers. Though AI promises much, at present, alleviating these biases and realizing its potential responsibly remains a work in progress.

Another major challenge will be finding the right talent and expertise to successfully implement, manage, and optimize AI in CRM systems. However, companies looking to stay ahead must invest in the experts who can support them on the journey. Amid the skills gap, outsourcing CRM specialists who can support companies with their goals, strategy, and integration will be key.

The bottom line

The promise of AI is real. However, there are challenges and due considerations must be made before businesses can begin implementation. Appropriate groundwork needs to be laid and companies must master the basics before moving on to the next new thing.

As the technology matures, it will unleash new levels of automation, insights, and prediction, strengthening experiences, improving decision-making, and boosting efficiency. With a strong CRM foundation in place, and staying ready with plans for integrating AI, businesses can transform how they acquire, engage and retain customers.

[To share your insights with us, please write to sghosh@martechseries.com]

The post Customer Service Meets Machine Learning: The AI-Powered Future of CRM appeared first on AiThority.

Large Language Models (LLMs) and Generative AI (Gen AI) are taking SaaS platforms to new heights. Customer Data Platforms (CDPs) in martech, for example, are currently at the center of every customer experience (CX) management discussion. In short, the AI inflection point in CDPs is here. With CX emerging as the core of any business decision today, there is an obvious need to redefine customer experiences through the lens of new-age technologies, including Gen AI and LLMs. Redefining CX means redefining CDPs. This is an important development for the CDP industry as it embraces the generative AI hype for its further growth. Speaking of growth, the CDP software market is expected to grow to $5.6 billion by 2026. Gen AI and personalization would grow by three times during the same time, according to a recent Martech Landscape trends report.

This is a huge opportunity for the CDP vendors who could completely change the way Martech users use the platforms for omnichannel CX management, contact center service automation, and building AI-powered customer journeys across new emerging channels, such as TikTok.

According to CDP expert, Rabid Raab, the use of modern cloud data warehouse technologies has led to a subtle shift in the perception of the CDP’s purpose. Raab mentions the importance of sticking to the fundamental definition of a CDP and its purpose. From the modern martech data management perspective, there is a need to redefine CDP as a “profile sharing system”, based on its identity as a packaged CDP or a warehouse CDP.

Historically, according to Google Cloud, marketing and advertising teams have relied on “packaged” CDPs to run their data management activities and then push the data into downstream martech and adtech tools for personalized customer experiences.

In 2024, this “redefinition” movement of packaged and warehouse CDPs can be achieved and consolidated in the martech stack by utilizing LLMs for CDP and generative AI.

By definition, a customer data platform is meant to be a seamless environment for integrating discrete data from multiple sources connected to the marketing technology stack. The sole objective of CDPs is to combine structured and unstructured (and anything in between) data to create a unified, singular customer profile. This profile is collected by ingesting billions of data points from multiple sources such as the company website, the internet, organizational ERPs, CRMs, DAMs, email, chat, mobile, and social media.

Here’s a graphical representation of different CDPs- traditional versus packaged versus composable CDPs. (source- Hightouch and Databricks).

The integration of CDP with different martech tools and ERPs through APIs and pre-built connectors. Using machine learning applications, it is possible to democratize data and analytics, making CDPs more agile, flexible, and scalable for multi-channel customer journey orchestration for different industries and technology landscapes such as Fintech, HR Tech, Sales tech, Martech, IT and Storage, and Cybersecurity.

The Emergence of Composable CDPs Using No-code AI Tools

Less than 60% of deployed CDPs are delivering any significant value to the martech teams. Thanks to the rise of modern data stacks and warehouses for CDPs such as Snowplow, Databricks, Hightouch, Google BigQuery, and AWS, composable architecture based on Reverse ETL would become the norm. In a recent AIThority article, Merkle’s Courtney Trudeau wrote about the emergence of Composable CDPs in the marketing technology landscape. To embrace experimentation as a culture in CDP deployment, generative AI is a big game-changer.

There’s room for the introduction of AutoML into composable CDPs so that data scientists can introduce unique AI-led instances for managing and governing data activation for big data organizations and their customers.

Generative Artificial Intelligence tools embedded into modern composable CDPs will replace traditional CDPs in 2024. These composable CDPs would emerge at the frontline of all major martech stacks that focus on customer journey mapping and audience profile segmentation. Composable CDPs can optimize existing data stacks with robust gen AI-powered no-code workflows, providing integrations with the top martech tools and SaaS applications to meet a wide range of business needs.

Popular data analytics tools provide instantaneous AI integrations with ChatGPT and other generative AI tools. Microsoft Power BI, Qlik Sense, Tableau GPT, Salesforce Einstein GPT, CoPilot AI, and Notion AI are examples that are worth naming in this domain.

Top AI CDP News: Hightouch Unveils Customer Studio, Extends the Power of the Cloud Data Warehouse to Marketing Teams

Utilizing Generative AI for Building a Real-time CDP

Redefining CDP and Generative AI applications for the martech landscape requires a flawless activation of real-time data analytics. Gen AI, powered by billions of real-time live-streaming data from multiple sources, can create interactive experiences delivered by virtual AI assistants.

According to mParticle, an AI CDP is built on these three capabilities:

1. High-quality first-party data collection across different streams;
2. Unifying this data to generate a 360-degree customer profile; and
3. Forwarding these AI-generated customer profiles to downstream Martech tools for activation.

CDP engineering teams could use Google BigQuery to build customer 360 for multi-channel engagements (including offline and metaverse). The BigQuery integration with CDP for customer 360 provides a strong foundation for real-time customer data analytics, 1:1 hyper-personalization, and compliance.

 AI Lakehouse and Google BigQuery have ensured CDPs get a unified architecture to arrive at a single true unified customer persona.

In-game advertising campaigns use CDP and generative AI tools to capture real-time customer intent.

Imagine you are watching your NFL game and suddenly feel the urge to drink your favorite cola during the match. You click on the cola ad, and voila! your smartphone app orders a cola drink for you, based on your latest click actions. Similar experiences can be found in interactive video games and live-streaming music concerts. Overall, this is possible by parsing customer data using generative AI, quickly sending a rippling stream of data analytics to create a personalized customer journey.

Martech stacks are incomplete without a real-time CDP. Adobe Real-time CDP is a great example in this space.

Adobe’s CDP is meant for full-funnel marketing, enabling martech teams to build customized journeys from acquisition through loyalty stages. Such CDPs help different customer-facing teams to prospect ever-changing digital personas and provide them with the best experiences — without the assistance of third-party cookies.

What’s behind this redefined CDP superpower?

Built on the Adobe Experience Cloud, Adobe Real-time CDP is a top-notch updated definition for CDPs and Gen AI integration.

Adobe’s proprietary AI platform, Sensei. Adobe Sensei GenAI for Real-Time CDP creates unique audience personas and launches activation campaigns using generative templates based on previous performances and profile matching. By continuously training with AI data, this CDP refines and improves audience definitions with more personalized outcomes for “in-the-moment” experiences.

Predictive Intelligence to Influence CX Journeys

With generative AI, Marketing organizations can embrace total CX transformation. This is capitalized on the composable CDPs with AI.

Recommended CDP News: New Acquia CDP Capabilities Spur CX Innovation for Customers and Partners Across Industries

Traditionally, Marketers relied on an army of CX specialists, CDP engineers, and AI programmers to scale their CDP orchestration. With the rise of LLMs in martech engineering, we are witnessing a surreal transformation of customer engagement strategies based on predictive intelligence.

Modern CDPs are required to do more than gather real-time insights from centralized, unified data. World-class AI CDPs generate predictive recommendations for automated decision-making based on unified customer data. Martech customers want their CDPs to orchestrate a bigger picture with deep data analytics and predictive intelligence. Gen AI-powered predictive intelligence can influence live customer segmentation by ingesting and integrating data via stream, batch, and interactive APIs.

CDPs such as Lemnisk use the RAMANUJAN AI ML capability to create moment-based CX via omnichannel customer touchpoints. This AI-powered CDP drives marketing automation efforts to understand ever-evolving buying intent and digital behaviors.

Sitecore’s David Schweer explains what a modern CDP looks like in the gen AI era. He defines it as a smart hub CDP that brings together data management, intelligence, and orchestration for reimagining the CX. New AI applications, including generative AI, trigger a range of predictive insights that help marketers design agile automation workflows for audience-building activities and modify marketing voice based on CX objectives. For example, Gen AI-powered customer data activation could be used to determine prescriptive churn and conversion predictions. Similarly, predictive intelligence could power other martech engines, such as AI-powered chat messengers or automated outbound emails.

Signal Discovery to Supercharge CDPs for CX

Marketers are finding new ways to capture experience signals to drive customer loyalty, enhance satisfaction, reduce churn, and maximize revenues. Signal Discovery in customer experience journeys are critical data points extracted from different martech systems. These click-stream data points could provide a complete picture through AI-driven conversation intelligence techniques for marketing, e-commerce, and contact centers. Invoca does it for Tealium’s AudienceStream CDP.

In June this year, Invoca’s generative AI capabilities were merged with its patented ML technologies to improve digital advertising and contact center performance running on CDPs. These Gen AI-led innovations promise to deliver an exceptional real-time conversation-driven CX with far better conversion rates than previously achieved with standalone martech tools. ChatGPT-based call summarization, smart alerting, and agent coaching are some of the biggest benefits of using CDP and generative AI to streamline signal discovery workflows in 2023. Different systems such as ERPs, CRMs, DAMs, ECMs, HRIS, and CDPs could work in sync to create a “playlist-looking” intelligent dashboard for compliance, auditing, and zero-party data insights.

Now that I have mentioned auditing, let’s talk about CDP security management with generative AI.

Customer Data Governance and Security Management using Gen AI

According to Tealium’s fourth annual report, titled “State of the CDP” 2023, companies with a CDP confide in their CDPs’ capabilities in meeting the current and future data privacy regulations. The same report also placed “privacy and regulatory compliance” among the top three CDP use cases, alongside customer retention, and customer acquisition.

Despite evident concerns related to the use of generative AI models for designing CDPs, business leaders feel this is a unique opportunity to push the boundaries in CX with prompt engineering and no-code LLMs. Heading into an AI-assisted CDP workflow means constantly brushing shoulders against cyber risks and data protection laws and principles. Trusted companies such as NVIDIA accelerate CDP developments using purpose-built tooling for agile experimentation, data analytics, and machine learning. Self-serving ML models can take care of the various IT requirements related to storage, network security, backup and recovery, data governance, and compliance. GPU accelerators from NVIDIA support CDP-ready configurations created for vendors who want to accelerate AI and ML training on their first-party data foundations and third-party apps.

Challenges for Generative AI Applications in the CDP Marketplace

LLMs are on a meteoric rise in the CDP landscape. Despite their immense popularity, IT leaders are averse to deploying generative AI to replace existing CDP models. There are two major reasons for this aversion in CDP and generative AI integration. The first reason is that it takes millions of dollars of computing resources to train AI models for high-end data management and activation. Generative AI can write limericks because it has been trained on trillions of data points related to limericks.

But, how many CDP engineering data points are available for training LLMs and generative AI models for this martech category? Our AIThority analysts are trying to find this out.

FAQs related to CDPs and AI

What are Customer Data Platforms (CDPs)?

Gartner defines customer data platforms (CDPs) as software applications that support marketing and customer experience use cases by unifying a company’s customer data from marketing and other channels. CDPs optimize the timing and targeting of messages, offers, and customer engagement activities, and enable the analysis of individual-level customer behavior over time.

According to Oracle, a CDP is packaged software that creates a comprehensive customer database accessible by other systems to analyze, track, and manage customer interactions.

How is a CDP different from a DMP?

There are four main differences between CDPs and DMPs. These are:

1. CDPs are used for the unification of data from marketing and non-marketing sources. DMPs unify data from advertising sources only. DMPs can’t provide insights on “personalization” and CX efforts in marketing.
2. CDPs collect all types of data. DMPs primarily collect only third-party data.
3. CDPs collect user’s personal information. DMPs collect only anonymized data.
4. CDPs store data for a very long time. DMPs retain this data for a very short time.

Adobe’s Real-time CDP is a unique platform. It provides the features of both DMP and CDP under the same roof.

Who are the biggest CDP vendors with AI offerings?

Salesforce, Tealium, Treasure Data, Adobe, Twilio Segment, and Informatica are some of the leading CDP vendors that offer AI capabilities for analytics, reporting, and predictive insights.

CDP and generative AI create a formidable combination to solve complex IT and marketing challenges. These are related to:

• Automated issue resolution
• Dynamic content creation for emails, website landing pages, surveys, product recommendations, and chat support
• Data cleanup
• Error identification and clean-up
• Co-programming for no-code self-service CX campaigns
• Customer segmentation
• Anomaly detection
• Data Enrichment
• Cybersecurity and privacy-related threat management

What are the top CDP use cases in 2023?

84% of marketers are putting significant effort into analyzing first-party data in 2023. This marks the origin of new use cases in the CDP marketplace. The top CDP use cases in 2023 are:

1. Unified Customer Data Analytics
2. Hyper-personalization
3. Customer Journey Mapping
4. Multichannel Messaging
5. Data Privacy and Governance (GDPR, CCPA, CA Delete Act, etc)
6. Generative AI / LLM Development

What are the top CDP vendor selection factors?

The top five factors while selecting a CDP vendor are:

1. Ease of use
2. History of successful CDP implementation/ user reviews
3. Single view of the customer
4. Meeting real-time data transfer requirements
5. Marketplace integrations
6. Customer service and support
7. Global locations and teams
8. Data privacy and compliance
9. Trust in CDP partnership

What kind of data does a CDP analyze for CX?

A CDP brings together first -, second – and third–party data together in one place. Modern CDPs also unify zero-party data to orchestrate hyper-personalized customer experiences in the B2B and B2C markets. A CDP gathers data from diverse data sources. These include ERPs, HRIS, e-commerce, CMS, CRMs, mobile websites, social media, apps, payments, and marketing automation platforms.

This is a useful reference related to the different types of data unified by a CDP. (source: Treasure Data)

Is a CDP the same as a Customer Engagement Platform (CEP)?

No, a CDP is different from a CEP.

A CDP enriches customer data and pushes the unique customer profiles into a CEP. The CEP uses the CDP-generated customer personas in different channels for orchestrating omnichannel CX campaigns. A CDP can also extract data from a CEP to build segmentations used for the creation of a unified customer profile. CDPs and CEPs can work in sync to enhance conversation intelligence and improve conversion rates.

What are the top CDP integrations that Martech users should have in 2024?

The top CDP vendors who offer AI-powered capabilities provide hundreds of customizable integrations to drive better CX. This is a useful directory of all CDP-related integrations that a martech team could refer to.

What are the key CDP marketplace trends for 2024?

CDP users are more likely to meet their marketing and customer experience objectives as compared to non-CDP martech users. CDP users are also 2x times more satisfied with their marketing outcomes as compared to the non-users.

Who owns the success of CDP initiatives?

IT teams are entrusted with the CDP deployments, and therefore, the CIO and the CTO share the primary responsibility for CDP’s success. With composable CDPs, the CDPs have become a shared resource across IT organizations. Therefore, the responsibility gets distributed among the CIO, CTO, CISO, CMO, and Chief Experience Officer. According to Tealium, 36% of CDP teams in 2023 consist of 6-10 people; 45% of CDP teams have 11+ people in their organization for the effective management of CDP.

So, riding on the generative AI hype, do you have a new definition for CDP in 2024?

[To share your insights with us, please write to sghosh@martechseries.com]

The post Riding on the Generative AI Hype, CDP Needs a New Definition in 2024 appeared first on AiThority.

The top companies driving AI adoption in the industry

HG Insights, the provider of go-to-market Technology Intelligence to 90% of tech companies in the Fortune 100, announced the release of the first annual HG Insights AI 1000TM — a ranking to guide business innovators with a holistic picture of the generative AI landscape and uncover opportunities in their markets.

HG Insights has been investing in solutions to help customers find success for thirteen years. As AI continues to evolve and revolutionize technology as we know it, HG is already providing customers with the insights they need to capitalize on the rapid growth in the generative AI market. The publishing of the AI 1000 is the next step that the industry-leading Technology Intelligence provider has taken toward moving the market forward.

“Investment in generative AI is moving quickly, with global technology vendors pouring hundreds of millions of dollars and massive computing power into the marketplace,” said Elizabeth Cholawsky, CEO, HG Insights. “The first annual AI 1000 list will unlock selling and buying opportunities for all companies in this fast-changing landscape.”

Recommended AI News: Aprimo Leads Next Generation of Collaboration With Groundbreaking AI-Powered Innovations

Identify Businesses Ready To Take The Next Step With AI

The age of AI is now. AI technologies are seeing massive investment across industries — from pharmaceuticals to manufacturing, media, electronics, energy, and more. Generative AI, the fastest-growing segment of AI tools, is a great example of this explosive growth: 60% of organizations using AI are using generative AI solutions and 40% plan to invest more in AI overall thanks to generative AI.¹

Distilled from billions of unstructured digital documents — the same that produce the world’s most sophisticated technology installation information, IT spend, contract intelligence, and intent data — the HG Insights AI 1000 provides insights into individual company’s AI readiness, adoption rates, intent to buy, industry and sub-industry, and revenue range. The data is comprised of:

• 466 distinct locations
• 48 distinct countries
• 548 AI technologies available for profiling

By uncovering what AI-related technologies a company is currently researching and evaluating, the AI 1000 list unlocks a breadth of opportunities for vendors who wish to leverage AI to gain a more significant share of their markets.

Rankings on the AI 1000 are based on HG’s patent-pending AI Maturity Index^TM, which includes insights from a specific company’s AI product adoption, the locations where adoption is detected, the strength of these detections, and the application of an Ideal Customer Profile of data-related product detections. This list is crucial for leaders to help identify companies whose technology stack indicates they’re ready to take the leap and capitalize on the wave of innovation in AI.

Recommended AI News: SurveyMonkey Announces AI Generated Surveys

Rankings on the AI 1000 are also based on the new patent-pending, machine-learning algorithms based on HG Insights’ Functional Area Intelligence^TM. We detect the footprint of departments and roles within a specific company (such as data science, data engineering, and data analysts) and chart how they change over time—on the individual, department, and organization levels. We can then determine which data science-related technologies are in use, where, and on what infrastructure.

HG’s Continued Investment in AI

AI has been making headlines lately, but at HG Insights AI has been the star for over a decade. The company has been leveraging AI for the past 13 years and has five pending patents. Building on this long history, HG is today exploring novel applications of AI as it continues to evolve and revolutionize technology as we know it.

“Generative AI will be the differentiator between competing companies and ultimately deliver a competitive advantage. The AI 1000 contributes to business value by illustrating new opportunities to increase revenue, reduce costs, better manage risk, and enhance productivity,” said Rob Fox, CTO, HG Insights.

Recommended AI News: Grammarly Defies the AI Hype With Significant Business Impact, Deepens AI Support for Enterprises

[To share your insights with us, please write to sghosh@martechseries.com]

The post HG Insights Publishes the First Annual AI 1000TM, Providing Insights into Individual Companies’ AI Maturity appeared first on AiThority.