Enterprises are investing heavily in diverse digital marketing methodologies. Television and radio advertisements are old news, so are advertisements interspersing YouTube videos and Spotify playlists. SMS and flash message/ call-based ads are automatically relegated to spam folder. Blog posts, guest posts, keywords, Search Engine Optimization (SEO), pay-per-click campaigns (PPC), social media marketing campaigns and Conversion Rate Optimization (CRO) continue to run strong, but the newest kids on the block are subtle product placement, in-game immersive advertisements, and interactable questionnaires/ activities.
Like almost all other economic spheres, digital marketing too has come to be significantly dominated by advances in Artificial Intelligence (AI). And Graphics Processing Units (GPUs) have become ingrained in the entirety of the digital marketing landscape, right from creating eye-catching unforgettable content to powering through the massive volumes of marketing data analytics.
This article will talk about the role of GPU-accelerated AI in digital marketing, and its current and potential usages. Read on!
Digital Marketing: A Primer
In simplest terms, digital marketing refers to the promotion of one’s products or services through digital channels. Any form of marketing that uses digital media channels and infrastructure to reach out to potential customers also comes under the aegis of digital marketing.
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But this is textbook definition. There is, in fact, much more to digital marketing than meets the eye. Enterprises today have begun relying on in-depth marketing analytics generated by search engines and social media conglomerates. Targeted advertising and personalized recommendations have transformed the entire landscape, whether on social media marketplaces or on e-commerce portals. SEO and CRO have slipped into everyday jargon. “Instagram influencer” is a new designation.
And guiding this transformation is data. Enterprises have always been aware of the potential of data. In the 1990’s and 2000’s, digital marketing was concerned merely with promoting relevant content across various channels and running marketing campaigns. The focus was to promote a brand or a business through search engines, emails, social media, YouTube, Facebook, word-of-mouth publicity, and other avenues.
But since then, the focus has shifted to data-driven targeted advertising. Data analytics is so irreversibly ingrained in marketing decision-making that the latter can no longer be imagined without the former. Enterprises are extracting actionable insights from the entire spectrum of data harvested from potential customers. Not only browsing history and e-commerce wish lists, but even location and movement data has a premium. The mere decision behind situating a billboard, once a straightforward process, is now also guided by data on traffic and viability. Digital marketing tools and campaigns have mushroomed and augmented their manifolds capabilities.
Modern digital marketing businesses use AI to generate quality marketing content, and to deliver effective and personalized advertisements to their respective demographics. The rationale for targeted advertising holds true as much for a restaurant as for a political party. GPU-accelerated AI is helping generate eye-catching video/gaming content, supporting analytics system backend, and automating the extraction of actionable insights. The end goal remains the same as it always was: bringing customers closer to the brand and its products and services.
AI and Intelligent Marketing
Every aspect of our lives is intertwined with AI. Even if you have been living under a rock bereft of technological developments and never have heard of Alexa, your money is kept safe in banks thanks mostly to AI/ ML systems preventing financial and insurance frauds and running algorithms to multiply that money manifolds!
On the other hand, as the competition to rank higher in web searches becomes fiercer, digital marketers have richly embraced the multifaceted capabilities of AI/ ML. They’ve been utilizing AI/ ML for
- Discovering innovative ways to get the advertising message across,
- Extracting penetrating insights from PPC campaigns and SM analytics,
- Playing around with keywords and niche ideas, and examining their effects
- Automating SM posts and email outreach,
- Reorienting marketing strategies instantaneously in response to customer churn
- Generating all-around better marketing investment returns
However, subjecting terabytes worth of data to analytics day in and day out would have been impossible without robust computing infrastructure (read GPUs). GPU-accelerated AI offers a cost-effective way to enhance marketing-led revenue and understand customer requirements. Other ways in which GPUs contribute to digital marketing optimization are as follows –
1. Generating comprehensive analytics
Every social media website, digital marketing tool and e-commerce platform extracts multitudes of user data and offers analytics and data visualization against various timelines and parameters. Thus, marketing personnel have access to a wide variety of customer data, from previous purchase history to browsing history and website bounce rates.
Insights gained from these humongous data sets facilitate informed marketing decisions, and AI/ ML can be trained to showcase brands and business products in line with customer’s browsing history and budget in one mouse click. The exhilarating data processing and data visualization features delivered by GPU further enables AI/ ML algorithms to be coded to aggregate diverse data sets, generate compelling content, and even suggest precise timelines to release said content for rich customer engagement.
Nvidia and Adobe are collaborating to develop an industry-leading GPU-accelerated AI program that can process massive amounts of user data, generate customer-centric content and boost business revenue.
2. Developing intelligent chatbots:
Chatbots are intelligent programs that operate according to pre-programmed responses fed to them. They mimic human-like conversations while interacting with customers. Intelligent, contextual chatbots have become significant for inbound marketing, boosting customer engagement, segmenting potential leads/ traffic, and assessing customer pain points.
AI and ML play a holistic role in chatbot development. Chatbots use Natural Language Processing (NLP) to comprehend and parse human queries and responses. ML algorithms can be written to design predictive chatbots that can understand customers’ context and intent and know in advance how to respond to different situations.
Chatbots can also be trained to learn from previous interactions and self-develop their intelligence for better marketing and business benefit. They can store and use past interaction data and other customer information for better context. Such dynamic chatbots with human-like intelligence require massive computational power both for supervised and reinforced training as well as for continuous operations with multiple simultaneous customers. Hence, the role of GPUs in intelligent chatbot development.
3. Predicting customer churn:
Through AI, digital marketing professionals can automate the extraction and collation of insights from different marketing channels. These insights can be monitored for measuring diverse marketing strategies’ traction with customers and the overall impact on the bottom line.
GPU can streamline the analysis of marketing performance data pertaining to MQL-to-SQL conversions, customer acquisition, and incremental sales boost. This is especially relevant for enterprises with numerous verticals and product lines.
More innovative enterprises have also been experimenting with GPU-simulated “digital twins”, i.e., virtual replicas of real-world production pipelines/ strategies, to study the consequences of any marketing/ design change decision and to effect strategy reorientation/ design correction in response to (virtual) feedback.
4. Enhancing content quality:
High-res videos, immersive animations and other graphics-rich content have become powerful means to convey a message or kickstart a marketing campaign. Such content engages audiences and boosts customer conversion. As the name suggests, GPU is the solution to any multimedia content development requirements. Content creators have been using GPU, dedicated and/ or integrated, for so long now that one automatically looks at the available graphics cards options when purchasing a PC/ workstation. Dedicated GPUs supply enormous compute power and on-chip memory to enable the creation of just about any kind of visual content, without any system lags or interruptions whatsoever.
5. Creating new content:
AI-generated content has revolutionized marketing and brand messaging. Content creators are using AI tools to churn out high-quality artworks, music, social media posts, creative writing, product descriptions, and even advertising ideas. Marketing departments worldwide are grappling with the question of inclusion of AI-generated content in their brand pages and campaigns. More enterprising companies are headhunting AI engineers to develop customized Generative AI solutions. Google too went through a series of flip-flops regarding allowing/ penalizing websites hosting AI content.
AI tools for automatic content creation require enormous processing power for development and deployment. ChatGPT, which exemplifies Generative AI taking the world by a storm, was trained using 20,000 Nvidia A100 GPUs. Its continued operation and commercialization will require 30,000 A100 GPUs, as per predictions.
Generative AI in Action: This image as well as the text in it was created using AI (Source)
6. Personalizing recommendations:
In the customer-centric age we inhabit, everything boils down to personalization. Friends/ followers are now recommended on social media platforms based on existing friend list/ interactions/ browsing history. E-commerce platforms suggest products based on browsing/ purchase history. And insurance companies offer plans and policies based on demographic/ location information. In short, the penetration of AI has changed the rules of the game. And GPUs have been silently supporting this onward march of billion-parameter ANN/ GNN-based ML model training.
Digital marketing first and foremost is concerned with understanding customers and enhancing brand recognition. Predictive analytics utilizes AI-extracted customer insights and sales segmentation for providing personalized recommendations, balancing various outreach methodologies, forecasting market changes, and influencing purchases. Digital marketing professionals are increasingly dependent on predictive analytics to mould marketing strategies in line with customer inclination and purchasing power to derive maximum engagement.
Conclusion
Artificial Intelligence is now intertwined with every technology that promises to ease our lives. Digital marketing has scaled new heights by incorporating AI and the massive computing power supplied by GPUs. Given the popularity of ChatGPT and other LLMs, even laypersons with no relation to AI or ANNs, are now experimenting with AI-generated content. These are heady days for digital marketing and marketing personnel must absolutely leverage the incredible design and analytics processing powers of GPUs to stay ahead of the curve.
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