However, for many consumer brands, the divide between expectations and reality looms large. Marketers envisioning a seamless, magical customer experience must recognise that AI’s effectiveness depends on high-quality underlying data. Without that, the AI falls flat, leaving marketers grappling with a less-than-magical reality.

AI-powered marketing fail

Let’s take a closer look at what AI-powered marketing with poor data quality could look like. Say I’m a customer of a general sports apparel and outdoor store, and I’m planning for my upcoming annual winter ski trip. I’m excited to use the personal shopper AI to give me an experience that’s easy and customised to me.

I need to fill in some gaps in my ski wardrobe, so I ask the personal shopper AI to suggest some items to purchase. But the AI is creating its responses based on data about me that’s been scattered across the brand’s multiple systems. Without a clear picture of who I am, it asks me for some basic information that it should already know. Slightly annoying… I’m used to entering my info when I shop online, but I was hoping the AI upgrade to the experience would make things easier for me. 

Because my data is so disconnected, the AI concierge only has an order associated with my name from two years ago, which was actually a gift. Without a full picture of me, this personal shopper AI is unable to generate accurate insights and ends up sharing recommendations that aren’t helpful.

Ultimately this subpar experience makes me less excited about purchasing from this brand, and I decide to go elsewhere. 

The culprit behind a disconnected and impersonal generative AI experience is data quality — poor data quality = poor customer experience. 

AI-powered marketing for the win

Now, let’s revisit this outdoor sports retailer scenario, but imagine that the personal shopper AI is powered by accurate, unified data that has a complete history of my interactions with the brand from first purchase to last return. 

I enter my first question, and I get a super-personalised and friendly response, already starting to create the experience of a one-on-one connection with a helpful sales associate. It automatically references my shopping history and connects my past purchases to my current shopping needs. 

Based on my prompts and responses, the concierge provides a tailored set of recommendations to fill in my ski wardrobe along with direct links to purchase. The AI is then able to generate sophisticated insights about me as a customer and even make predictions about the types of products I might want to buy based on my past purchases, driving up the likelihood of me purchasing and potentially even expanding my basket to buy additional items. 

Within the experience, I am able to actually use the concierge to order without having to navigate elsewhere. I also know my returns or any future purchases will be incorporated into my profile. 

Because it knew my history and preferences, Generative AI was able to create a buying experience for me that was super personalised and convenient. This is a brand I will keep returning to for future purchases.

In other words, when it comes to AI for marketing, better data = better results.

So how do you actually address the data quality challenge? And what could that look like in this new world of AI?

Solving the data quality problem

The critical first element to powering an effective AI strategy is a unified customer data foundation. The tricky part is that accurately unifying customer data is hard due to its scale and complexity — most consumers have at least two email addresses, have moved over eleven times in their lifetimes and use an average of five channels (or if they are millennials or Gen Z, it’s actually twelve channels).

Many familiar approaches to unifying customer data are rules-based and use deterministic/fuzzy matching, but these methods are rigid and break down when data doesn’t match perfectly. This, in turn, creates an inaccurate customer profile that can actually miss a huge portion of a customer’s lifetime history with the brand and not account for recent purchases or changes of contact information. 

A better way to build a unified data foundation actually involves using AI models (a different flavour of AI than generative AI for marketing) to find the connections between data points to tell if they belong to the same person with the same nuance and flexibility of a human but at massive scale. 

When your customer data tools can use AI to unify every touchpoint in the customer journey from first interaction to last purchase and beyond (loyalty, email, website data, etc…), the result is a comprehensive customer profile that tells you who your customers are and how they interact with your brand. 

How data quality in generative AI drives growth

For the most part, marketers have access to the same set of generative AI tools, therefore, the fuel you input will become your differentiator. 

Data quality to power AI provides benefits in three areas: 

• Customer experiences that stand out — more personalised, creative offers, better customer service interactions, a smoother end-to-end experience, etc.
• Operational efficiency gains for your teams — faster time to market, less manual intervention, better ROI on campaigns, etc.
• Reduced compute costs — better-informed AI doesn’t need to go back and forth with the user, which saves on racking up API calls that quickly get expensive

As generative AI tools for marketing continue to evolve, they bring the promise of getting back to the level of one-to-one personalisation that customers would expect in their favourite stores, but now at a massive scale. That won’t happen on its own, though — brands need to provide AI tools with accurate customer data to bring the AI magic to life.

The dos and don’ts of AI in marketing

AI is a helpful sidekick to many industries, especially marketing — as long as it’s leveraged appropriately. Here’s a quick ‘cheat-sheet’ to help marketers on their GenAI journey:

Do:

• Be explicit about the specific use cases where you plan to use data and AI and specify the expected outcomes. What results do you expect to achieve?
  
• Carefully evaluate if Gen AI is the most appropriate tool for your specific use case.
  
• Prioritise data quality and comprehensiveness — establishing a unified customer data foundation is essential for an effective AI strategy.

Don’t:

• Rush to implement GenAI across all areas. Start with a manageable, human-in-the-loop use case, such as generating subject lines.

(Editor’s note: This article is sponsored by Amperity)

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With mounting research demonstrating that gender diverse teams outperform their peers time and time again, we turned the conversation over to the exceptional women thought leaders who are at the forefront of shaping the narrative surrounding Gen AI and marketing. 

Let’s dive into their insights and experiences:

Lisa Gately, Principal Analyst at Forrester 

Gately has 20 years of experience in B2B technology content, communications, events, and services marketing. She helps Forrester clients build and optimise their B2B content engines and transform them into competitive differentiators. Lisa is an evangelist for audience-centric content strategy, content marketing, and content operations.

“During the past year, we’ve seen Gen AI capabilities appear in the martech stack along with a rise of multimodal capabilities, where AI models can understand, interpret, and generate content across multiple formats like text, images, audio, and video. It can be overwhelming to understand which systems do what tasks and to determine which ones to embrace. However, making time to learn about these capabilities is important. Gen AI brings more power to content creation, audience engagement, and personalisation. Content use cases aren’t only a practical entry point for scaling Gen AI adoption; they also represent a large part of an organisations’ activities and offer enormous potential for enhancing the customer experience and speeding time to market. Acting now is essential because the pace of change for Gen AI will only accelerate.”

Julie Shainock, Managing Director Travel, Transport & Logistics (TTL) at Microsoft

Shainock is responsible for developing Microsoft’s point of view and future strategy for our WW Travel and Transport Industry. She is focused on leading the airlines, hospitality companies, cruise and freight logistics and rail companies to driving innovation that will enhance the customer and employee journey, while driving increased productivity and cost reduction with the use of Microsoft’s technology and its ecosystem of solution partners.

“Generative AI is set to revolutionise the travel, transport, and logistics industries by delivering unprecedented levels of personalisation, efficiency, and innovation. It’s not just about automation; it’s about creating intuitive, seamless customer experiences and unlocking new levels of operational efficiency. For organisations to tackle the full potential of Gen AI effectively, establishing a clean data foundation and a clear strategic vision for desired outcomes is critical.”

Adiela Aviram, Cookieless Marketing Transformation Practice Leader at Deloitte Digital

Aviram is an award-winning digital marketer and a Senior Manager in Deloitte Digital’s Advertising, Marketing and E-Commerce offering. Beyond her career, she is a dedicated Fellow at The Black Wealth Club (BWC), actively contributing to the group’s mission of wealth generation and community reinvestment.

“The only thing constant in marketing, much like in every field, is change. Reflecting on one of my initial roles as a search marketer, I can draw some parallels. I had no formal training in search marketing, and the idea of learning an entire system to advertise on search engines seemed bizarre. Now, much of that same field is supported by generative AI. I’m excited for all the things Gen AI will enable for marketers. It will allow us to focus on more strategic, less repetitive, and energizing areas of our work. However, marketing will always need the human element. Customer experience, by its very nature, is human, and Gen AI will not stand in the way of that.” 

Joyce Gordon, Head of Generative AI, Amperity

Gordon leads Amperity’s generative AI product development and strategy. She’s also worked on the product development for many investments across the ML and ML Ops spaces, including launching Amperity’s predictive models and infrastructure used by many of the world’s top brands.

“Gen AI is only as good as the data that powers it. And since customer data is notoriously complex, it takes a different AI process to unify it into accurate, comprehensive profiles that can feed your Generative AI tools to get the best results.  

Customer data tools can use AI to power critical processes behind the scenes, including data unification, insights, and predictions, so you have the answers to the questions “Who are my customers? What did they do? And what should I do next?” 

In a world where the same Generative AI tools for activation are available to everyone, the data you feed into your Gen AI systems will be a key competitive differentiator, since it determines the quality of the output. In short, it’s not enough to have AI tools at the last mile — it needs to be part of your approach from the first step.”

Teresa Sperti, Founder & Director, Arktic Fox

Sperti is a highly seasoned and regarded digital and eCommerce leader with over 20 years’ experience working with and for leading brands including Coles, Officeworks and World Vision among others. Since establishing Arktic Fox four years ago, Teresa and her team have been partnering with leading brands and scale up retailers and CPG | FMCG brands to drive eCommerce adoption and capability build, to enable better utilisation of data to enhance experience and deliver better omnichannel experiences and supported brands to utilise and invest in tech to underpin their strategy.

“There are pivotal moments in the digital era that fundamentally alter the trajectory of the industry – the birth of social media and the launch of the iPhone were some of those moments. And I believe the launch of ChatGPT is another one that really lit a match to the adoption of Gen AI.

“In the tech world, we are already seeing strong adoption of Gen AI within marketing platform interfaces to automate creative development and support and enable smarter decision making. However, it is still very much the early days for Gen AI , and I think we’re just scratching the surface. Brace yourself for a whirlwind of change in this space over the next 12 to 24 months.”

The future of Gen AI in marketing

The female leaders in marketing have spoken, and their insights demonstrate the importance of embracing Gen AI not only as a tool for innovation but as a fundamental pillar for cultivating growth and establishing meaningful relationships within the rapidly transforming marketing landscape. Let’s make 2024 the year we harness Gen AI to its fullest potential and unleash lasting, genuine change for the better.

(Editor’s note: This article is in association with Amperity)

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The adoption of AI is rapidly gaining momentum, with 35% of businesses currently utilizing AI-powered solutions. This trend is mirrored in the wider world, where 77% of devices in use feature some form of AI. Recognizing the competitive advantage that AI can bring, 9 out of 10 organizations support the adoption of AI. The future looks bright for AI, with projections estimating that AI will contribute a staggering $15.7 trillion to the global economy by 2030.

How can we use AI in marketing?

Incorporating AI into marketing involves leveraging the transformative power of technology to enhance various aspects of the marketing landscape. AI redefines how businesses connect with their audiences, from predictive analytics and personalized customer experience to automated decision-making and tailored messaging. This section delves into the diverse ways AI can seamlessly integrate into marketing strategies for achieving optimal results.

Best 10 AI marketing campaign examples in 2023

As artificial intelligence (AI) revolutionizes the marketing landscape, businesses are embracing its transformative power to drive effective marketing strategies and enhance digital marketing efforts. Dive into this exclusive showcase of 10 groundbreaking AI marketing campaigns that highlight the immense potential of AI to connect with audiences, boost engagement, and achieve business objectives. These case studies demonstrate how artificial intelligence can be seamlessly integrated into various marketing channels, propelling businesses toward success.

1. Heinz: AI-Generated Ketchup

Heinz, a renowned condiment brand, embraced the generative AI craze by asking a simple question: “What does AI think ketchup looks like?” They turned this question into a viral marketing campaign, using the AI image generation tool DALLE-2 to create fun and engaging images of ketchup in various settings. To further engage their audience, Heinz encouraged social sharing, allowing users to create their own AI-generated social media posts with ketchup images.

2. Ben & Jerry’s: Breakfast Flavors Discovery

Ben & Jerry’s, a leading ice cream brand, partnered with Unilever’s AI-powered trend analysis to uncover a gap in the market for breakfast-inspired ice cream flavors. Based on this data-driven insight, Ben & Jerry’s launched their “ice cream for breakfast” campaign, introducing three new flavors that resonated with consumers.

3. Shopify: AI-Powered Shopping Assistant

Shopify, a leading e-commerce platform, introduced an AI-powered shopping assistant chatbot to enhance the user experience. This chatbot can guide users through the vast selection of stores on Shopify, offering personalized recommendations and assistance.

4. Coca-Cola: Create Real Magic

Coca-Cola, a beverage giant, launched a creative AI-powered contest called “Create Real Magic.” This contest invited digital artists to create art pieces using an AI-powered web app, with the top entries featured on Coca-Cola’s digital billboards in Time Square. This collaborative campaign showcased the power of AI to foster creativity and engagement.

5. Nutella: Unica Limited Edition Labels

Nutella, a popular hazelnut spread, sought to stand out with unique and personalized packaging. Working with Ogilvy Italia, Nutella leveraged AI to create 7 million one-of-a-kind labels, each reflecting the diverse and expressive Italian culture. This campaign demonstrated the power of using AI in marketing to enhance product differentiation and brand appeal.

6. Volkswagen: AI-Powered Ad Buying

Volkswagen, a renowned automotive manufacturer, adopted a groundbreaking approach to optimize its ad-buying decisions. By leveraging AI, Volkswagen implemented an automated system that analyzes real-time data to identify the most effective ad placements and target audiences. This data-driven approach, 

artificial intelligence in marketing enabled Volkswagen to reduce its ad spend by 20% while increasing sales.

7. Netflix: Personalized Recommendations

Netflix, a leading streaming service, revolutionized the way users discover content by employing AI-powered personalization algorithms. These algorithms analyze user behavior and preferences to recommend relevant movies, TV shows, and даже artwork that aligns with individual tastes.

7. Mastercard: Crayon AI for Competitive Intelligence

Mastercard, a global payments company, faced the challenge of staying ahead of the curve in an ever-evolving competitive landscape. To gain a deeper understanding of competitor strategies and anticipate market trends, Mastercard integrated AI into their business operations. By employing Crayon, an AI-powered competitive intelligence platform, Mastercard gained a clear picture of its competitors’ activities and market movements. This insights-driven approach empowered Mastercard to make informed business decisions and protect its market position.

8. Nike: Immersive AI-Generated Match

Nike, a sportswear brand, collaborated with Serena Williams to create an AI-generated match that juxtaposed her younger self from 1999 against her modern self from 2017. This award-winning campaign commemorated Nike’s 50th anniversary and showcased the emotional connection that AI can evoke.

9. BMW: Projecting AI Art onto Cars 

A luxury car manufacturer, BMW partnered with an advertising agency to project AI-generated art onto their 8 Series Gran Coupé. This innovative campaign aimed to connect with BMW’s target audience on an emotional level and highlight the brand’s creativity and innovation.

10. Calm App: Personalized Content Recommendations

Calm, a popular meditation app, leveraged Amazon Personalize, an AI-powered product recommendation engine, to provide personalized content recommendations to users. This dynamic approach ensures that users are presented with relevant content that aligns with their preferences, enhancing the overall user experience.

These ten examples demonstrate the transformative power of AI in marketing, highlighting its ability to drive innovation, personalization, and data-driven decision-making. As AI continues to evolve, its impact on marketing is expected to grow even more profound, paving the way for even more creative and effective marketing campaigns.

In conclusion

From Heinz’s creative use of AI-generated images to Ben & Jerry’s data-driven flavor launch, these examples showcase how AI can be applied to shape personalized customer experiences, optimize ad targeting, and personalize content recommendations. By harnessing the power of AI, business can elevate their AI marketing strategy to unprecedented heights, achieving deeper customer engagement, enhanced conversion rates, and a competitive edge in the ever-evolving digital marketplace.

To further explore the role of AI in marketing and witness groundbreaking campaigns, consider reaching out to a leading AI marketing agency. With their expertise and guidance, you can unlock the full potential of AI and transform your marketing campaigns into resounding successes.

To conclude, the era of AI in marketing presents a world of unprecedented opportunities to transform data into gold. By embracing AI-based marketing campaigns, businesses can not only stay ahead of the competition but also revolutionize how they connect with their audience, paving the way for a future where data truly becomes a valuable asset in the marketing realm.

(Editor’s note: This article is sponsored by Digital Agency Network)

The post Turning data into gold: 10 exceptional AI marketing campaign examples appeared first on AI News.

The focal point of Smith’s presentation was a strategic experiment conducted by his team to explore the potential of AI in reducing noise and bias inherent in decision-making. Smith began by addressing the common perception of decision-making and the often-overlooked influence of human biases and external factors.

“Let’s recognise that we’re not the best at making decisions, that there are some issues when we make decisions—just as there are some issues when AI makes some decisions,” said Smith.

Smith advocates for combining the strengths of both human and AI decision-makers.

The strategic experiment involved a comprehensive analysis of the human decision-making process, where the team pitted AI against a human team in running a Facebook travel campaign. Smith delved into the intricacies of the human brain’s dual components—the amygdala for intuitive thinking and the prefrontal cortex for reasoning.

Notably, Smith drew attention to the concept of “noise,” a term he differentiated from bias, describing it as the variance in decision-making that introduces inconsistencies. He supported this with examples from various professions, such as judges delivering differing sentences based on external factors.

The challenges within the marketing and advertising space were highlighted, particularly the difficulty of managing a vast number of variables—illustrated by a campaign with a staggering 83 million variations.

“There’s no way that a human can realistically go through 83 million [ad variation] combinations,” said Smith. “AI is better at picking out important signals in large data sets.”

Initially, the results of the strategic experiment showed humans outperforming the AI-optimised campaign, However, the AI campaign quickly pulled away:

While acknowledging AI’s flaws — including bias — Smith advocated for a collaborative approach, envisioning a balance between human intuition and AI assistance. He highlighted the importance of recognising human limitations and leveraging AI to reduce decision-making flaws.

The presentation concluded with key takeaways, encouraging the recognition of human decision-making limitations, leveraging AI to reduce flaws, and finding the right balance between human input and AI assistance.

See also: Ampere Computing: Unlocking a Path to the Sustainable Cloud

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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How to create a digital marketing strategy with AI

AI has opened up a vast array of new possibilities for digital marketers, enabling them to gain competitive advantages and engage with customers in innovative ways. Among such tools are artificial intelligence marketing platforms, which in essence, are software that leverage AI technology to perform tasks and help marketers make insightful business decisions.

From predicting customer behaviour to automating tasks, AI marketing tools can help marketers save time, increase efficiency, optimise efforts, and boost ROI by identifying patterns from historical marketing data. 

In this article, we’ll delve into the world of AI marketing strategy, exploring how to create a powerful digital marketing plan by harnessing AI-driven tools and technology.

The power of AI in marketing

Using AI for marketing has rapidly become a game-changer in the world of digital marketing. Its ability to process vast amounts of data, analyse patterns, and make real-time decisions has made it an indispensable tool for marketing teams. Here’s how you can harness the potential of AI to supercharge your marketing strategy:

1. Understand your target audience

One of the primary advantages of AI in marketing is its ability to analyse customer data comprehensively. With AI-driven tools, you can gain valuable insights into consumer behaviour, preferences, and buying patterns. This information is instrumental in creating highly targeted marketing campaigns that resonate with your audience.

2. Personalise content

AI technology enables you to personalise your content like never before. By analysing user data, AI can tailor marketing messages and product recommendations to individual customers. This personal touch not only enhances the customer experience but also boosts conversion rates.

3. Content generation

Creating engaging content is a fundamental aspect of any marketing strategy. AI can assist marketing teams by generating content ideas, optimising headlines, and even drafting articles. This streamlines the content creation process, allowing marketers to focus on strategy and creativity.

4. Real-time decision-making

In the fast-paced world of digital marketing, timing is crucial. AI can analyse data in real-time, helping you make informed decisions on when and where to run your marketing campaigns. This ensures that your efforts always align with the latest trends and consumer behaviour.

Now that we’ve explored the incredible potential of AI in marketing, let’s dive into the tools of AI for marketing strategy.

Seven best AI tools that help you to create a marketing strategy

Adzooma

Adzooma stands as a formidable AI marketing ally, offering an array of invaluable benefits for optimising your AI marketing strategy. With its AI-powered recommendations, it seamlessly identifies avenues for enhancing campaign performance. The platform’s automation capabilities extend to managing bid adjustments, fine-tuning keyword targeting, and conducting ad copy tests, significantly streamlining your campaign management tasks. By harnessing Adzooma, not only do you achieve time efficiency, but you also elevate the effectiveness of your AI marketing endeavours, yielding superior results.

Jasper

Jasper AI, formerly recognized as Conversion.ai, represents an advanced AI marketing solution tailored for crafting top-notch content across various channels, including social media, email, landing pages, and articles. It harnesses the capabilities of the GPT-3 model developed by OpenAI to transform text into engaging copy. Marketers can effortlessly generate compelling content by supplying input such as brand or product names. With this potent AI marketing tool, businesses spanning diverse sectors gain the capacity to craft more convincing, alluring content for their blog posts, landing pages, social media, advertisements, marketing emails, and beyond.

HubSpot

HubSpot’s AI tools empower marketers to unlock new levels of creativity and precision in their campaigns, ultimately driving enhanced engagement and results. Transform your marketing approach with HubSpot’s cutting-edge AI capabilities. Marketers now have access to powerful tools that facilitate content creation, campaign personalization, and data analysis, enabling the development of precise and influential marketing strategies. Additionally, it assists in crafting social media posts and generating images based on user prompts, ensuring that your marketing efforts are streamlined, efficient, and highly impactful. 

Murf AI

Murf stands as an AI voice synthesiser, ranking among the foremost AI marketing solutions. It empowers marketers to generate lifelike speech through natural language processing, eliminating the necessity for specialised hardware. This AI marketing solution streamlines marketers’ processes, facilitating the swift creation of audio and video content for various applications, such as social media, brand advertising, and marketing initiatives, all within a matter of minutes.

Adobe Sensei

Adobe’s commitment to innovation ensures that brands can leverage AI-driven marketing solutions to elevate their customer experiences, paving the way for enhanced engagement and loyalty. As a pioneering force in artificial intelligence, we recognise that generative AI holds the power to revolutionise all facets of marketing, spanning the realms of strategy, implementation, and analysis. With the introduction of Adobe Sensei GenAI, their latest AI technology, customer experience teams can harness the innate capabilities of generative AI. This empowers them to amplify their expertise and deliver customer journeys that are not only more precise but also deeply personalised. 

ClickUp

The introduction of ClickUp AI marks a transformative moment for marketing and sales units, offering enhanced efficiency, seamless collaboration, and expedited workflows. This innovative feature within ClickUp introduces AI capabilities that are poised to revolutionise the way teams operate. From streamlining processes and fostering creativity to facilitating project management and igniting innovative thinking, ClickUp AI is the catalyst for optimising productivity and content quality, all while ensuring consistency and scalability.

SurferSEO

SurferSEO is an AI-powered SEO tool that helps you optimise your content for search engines. It analyses the top-ranking pages for your target keywords and provides you with insights into their content structure, word count, and other factors. You can then use this information to create content that is more likely to rank well.

Final thoughts

As AI technology continues to evolve, its role in marketing will only become more prominent. By harnessing the power of AI-driven tools and technology, you can create a dynamic and data-driven marketing strategy that not only reaches your target audience but also engages them on a personalised level. Embrace the future of marketing with AI and elevate your brand to new heights.

Looking to revamp your intelligent automation strategy? Learn more about the Intelligent Automation Event & Conference, to discover the latest insights surrounding unbiased algorithyms, future trends, RPA, Cognitive Automation and more!

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Using artificial intelligence, Mona Lisa, the Statue of Liberty, and other iconic tourist attractions come to life with a simple message: Don’t come see me – visit Denmark instead. Other than its cheeky approach, the campaign stands out by being completely written by artificial intelligence.

“Imagine that you are Mona Lisa. Write a speech on why people should visit Denmark instead of standing in line to see you.“

This was the prompt given to an artificial intelligence to create the script of one of a series of videos in which tourist attractions from all over the world turn against themselves and recommend visiting Denmark – rather than standing in line at the Louvre or seeing the Statue of Liberty in a sea of selfie-sticks. Executing on the brand campaign ‘Don’t be a tourist – be an Explorist’, VisitDenmark positions Denmark as the antidote to bucket list tourism.

Louis Pilmark, creative director at Danish advertisement agency Brandhouse/Subsero, said: “Having iconic attractions from popular tourist destinations turn on themselves is a good way to highlight the absurdity of doing and seeing the same things as everyone else. Who better to explain it, than the paintings and statues that see millions of tourists every year.  

Iconic art meets trending tech

Other than the slightly teasing approach, the campaign is unique in that both the scripts and the visuals are created by artificial intelligence. While the new techniques like deepfake and motion synthesis have been used to bring images to life in the last couple of years, the addition of scripts generated completely by AI makes it one of the first campaigns to combine the two technologies.

Kathrine Lind Gustavussen, senior PR at VisitDenmark, said: ”The scripts are 100% generated by AI – we didn’t write a single word, we only removed parts and bits that were too long or simply not true. While it felt somewhat risky to put our entire messaging in the hands of artificial intelligence, we’re excited to be at the forefront of the tourism industry, using cutting-edge technology to bring our creative visions and messages to life.” 

Tourist attractions aren’t so attractive anymore

The overall campaign, developed by London-based creative agency Fold7 builds on an insight that bucket list tourist has lost its lustre. A study conducted in the UK, Sweden and Germany validated our hypothesis that ‘feeling like a tourist’ would ruin a holiday. More than half of the respondents agreed that overcrowded tourist sites and landmark were a reason for holiday disappointment.

Yelena Gaufman, strategy partner at Fold7, said: “Denmark may not be a bucket list destination and the wonders there aren’t big and dramatic, but they are small and plentiful. We saw this as a huge opportunity to attract a different kind of traveller, the anti-tourist, the Explorist.”

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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The new offering targets data practitioners and non-technical users such as in marketing, sales, and revenue operations teams to build data pipelines within minutes. For example, it provides operations teams with a fast, free, and frictionless way to load, integrate and analyze high-quality campaign, pipeline, forecast, and revenue data. In addition, data analysts and data engineers benefit from increased productivity and rapid development. 

This is the second in a series of releases that began with the Informatica Data Loader launch in May 2022. Taken together, Informatica Data Loader, Cloud Data Integration-Free (CDI-Free), and PayGo (CDI-PayGo) are the industry’s only free data loading and integration solutions. They are natively built in to provide intelligent cloud data management services for all your data-driven use cases. Informatica CDI-Free, CDI-PayGo and Data Loader support all major data warehouses/lake solutions, including Amazon Redshift, Azure Synapse, Databricks Delta Lake, Google BigQuery, and Snowflake.  

Jitesh Ghai, chief product officer at Informatica, said: “We are redefining the data integration market by making it free, easy to use and accessible to everyone. Organisations face the challenge of ingesting huge volumes of data from disparate sources and then making sense of that information. There is a clear need for no setup and no code SaaS data integration tools that are free and pay-as-you-go to quickly get started serving both business-focused data engineers and non-technical business users and analysts.

“By giving business and non-technical users access to simple, cost-optimised data integration solutions, organisations can bring the power of data to the masses.”   

The key to a truly data-driven business is providing self-service data integration to users across the organisation in technical and business roles. Informatica CDI-Free and PayGo provide just that: 

• CDI-Free: A free service that allows users to process up to 20M rows for ELT or reach 10 processing hours for ETL, per month, whichever comes first. 
• CDI-PayGo: All the capabilities of CDI-Free with no limit on processing rows or hours of usage. CDI-PayGo comes with essential customer support and SOC2 compliance. In addition, users only pay for what they use with a credit card.  

Users benefit from easy setup, and usage of these data integration services with AI-powered automationnon – need for coding, setup, or any DevOps. In addition, the cloud data loading and integration ETL/ELT services can be easily accessed from each of Informatica’s ecosystem partners including Amazon Web Services, Databricks, Google Cloud, Microsoft Azure and Snowflake.  

Chris Eldredge, VP of data office at Paycor, said: “The ability to harness the power of data is a valuable competitive advantage. Having the right data integration platform enables a data foundation that drives agility, insights, and innovation for superior business results. The new Cloud Data Integration (CDI)-Free and PayGo products lower the barriers to get started with data integration.  These new products will open the door for more data professionals, including tech-savvy business users, to leverage best-in-class data integration tools from Informatica.” 

Matt Wienke, CEO of Infoverity, said: “Cloud Data Integration (CDI)-Free and PayGo are launchpads that will improve and serve those entering the data integration domain. The tools are intuitive to use and easy to navigate. CDI-Free will empower tech-savvy business users to begin moving their data to the cloud without committing to software costs. Furthermore, the option to scale up to Informatica’s enterprise-grade cloud platform minimises risks from the trial and adoption of these products.” 

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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Algorithms based on artificial-intelligence (AI) can be tailored to brands’ unique goals, allowing marketers to find pockets of performance within vast amounts of data and optimise media buying to drive real business outcomes. By combining custom AI approaches that integrate a brand’s key performance indicators (KPIs), and shaking off our third-party cookie dependence, we can welcome a new era of transparent and effective programmatic media.

User matching via first-party data signals

One way AI and custom algorithms will shape media buying, is by matching converted consumers with prospects that have similar digital patterns. Rather than focussing on who consumers are – their age and gender, or where they live – AI looks beyond basic characteristics to focus on the most important behavioural signals of a likely customer. Two consumers can have completely different profiles but ultimately want the same thing. Where traditional audience targeting would miss this opportunity, algorithmic matching enables brands to identify and take advantage of these similar needs.

Algorithmic consumer matching is currently based on first-party data signals, from retailers, brands or publishers. Moving forward, an explosion in new types of data is expected from connected cars and homes, internet-of-things devices, virtual and augmented reality, and biometrics, which will all feed into this process. AI will be vital to manage this data, and there must always be an emphasis on balancing the relationship between AI and ethics to ensure advertising works better for everyone while individual identities are protected.

Aligning media buying with brand objectives

A second way tailored algorithms will make media buying more effective is by aligning activity with brand objectives to deliver real business performance. Brands decide on the outcomes they want to achieve, allowing multi-metric KPIs and offline data inputs to be integrated into customised algorithms and ensure media buying is focussed on attaining those goals.

AI can increase efficiency by automatically directing spend towards areas of strong performance. The technology constantly checks itself to shift delivery and improve execution. Algorithms can predict which impressions will perform well, based on a huge variety of factors such as the length of time since a user visited an advertiser’s website, and generate far better conversion rates than can be achieved though manual optimisation.

In addition, once desired outcomes are established, custom algorithms can run thousands of real-time tests to determine the exact bid required to win media placements in an ad exchange. The performance of media buys can be continually measured, with results fed back into algorithms to create a closed loop of optimisation.

While AI is vital to enhance and streamline digital media buying, it doesn’t remove people from the process by any means. Success relies on the initial input and continuous management of campaigns by highly skilled people from data scientists to media planners. Algorithmic success is about finding harmony between man and machine by optimising towards goals set and overseen by real people to ensure ethical application of technology.

Dynamically optimising creative for performance

The role of custom algorithms doesn’t end with buying the right impression at the right price, it also includes ad execution, and specifically optimising ad creative to maximise the chances of conversion. Sophisticated algorithms are used to select the most relevant and effective creative elements, according to a variety of data points, and to assemble ads that appeal to individuals at different stages of the purchase journey.

Volvo, for instance, recently used AI to generate cost-effective conversions from a digital advertising campaign in Norway. Custom algorithms were used to test creative elements such as logos, layouts, and messaging at scale to determine which creative versioning drove the most conversions at the lowest cost. As a result, Volvo saw a 440% increase in audiences configuring new cars and booking test-drives and made more efficient use of its marketing budget with a 66% reduction in cost-per-acquisition (CPA).

As technologies evolve and volumes of data increase in digital advertising, the creative applications of custom algorithms will continue to grow in ways we may not be able to imagine yet. What we can be sure of, is that AI will be a necessary component in the toolbox of any marketer looking to optimise media buying, and better deliver business outcomes.

Find out more about Digital Transformation Week North America, taking place on November 9-10 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

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