First step: look at your IT infrastructure

Startups tend to go for on-the-fly experimentation and often select separate GenAI tools. However, the pillar of any AI transformation is a proper IT infrastructure. CRM, automation, analytics, and content management systems were considered the basics for successful marketing strategies. But the new reality is different. Performance depends on AI-driven decisions, predictive modelling, and automated customer interactions. Startups need an IT infrastructure supporting real-time data pipelines.

How is evolving the MarTech stack?

• AI-powered CDPs, such as Segment and Adobe Experience Platform, are able to synchronise and activate data across multiple channels
• Many companies still rely on outdated batch-processing automation tools. AI works for campaign orchestration and coordinates them across paid, owned, and earned media
• AI works miracles for attribution models. Platforms like Neustar and Fospha can track ROI using AI-driven attribution models using unified real-time data from marketing teams
• Content creation is another popular AI use. Different tools (including Jasper, Copymatic, and Copy.ai) create SEO-optimised content and creative content for social media

GenAI advantages: from personalisation to idea generation

McKinsey specifies current uses of Gen AI in marketing mostly include off-the-shelf pilots integrated into existing workflows. What are its key values for businesses?

• Personalisation of marketing campaigns to improve engagement rates and provide higher quality content. Probably the most well-known case is Netflix. Streaming platforms use AI algorithms to analyse users' viewing history, ratings, and preferences
• Analysing unstructured customer data helps marketers to understand customer behaviour, interpret feedback and provide product recommendations. Businesses are able to create dynamic consumer profiles updated in real-time since machine learning (ML) analyses micro-interactions, and natural language processing (NLP) can process contextual sentiment data
• Process automation: from resolving customer tickets to higher-level interactions
• Opportunity identification and idea generation. Gen AI helps marketers to analyse competitor moves, assess consumer sentiment, and test new product opportunities
• GenAI reduces time to market by up to 50% by automating content generation, including text, photo and video content

Unified data platforms for marketers

Data quality and consistency can become a challenge since AI models heavily rely on accurate data to produce meaningful insights, especially for Customer Data Platforms (CDPs). I recommend unified data platforms designed to enhance content, sentiment detection, and personalised user interactions. First of all, we made a full data audit and traced information flow between CMS platforms, HubSpot marketing automation, and Salesforce CRM. The platform components then included:

• Modern CDPs compile and integrate customer data from several sources, including websites, mobile apps, CRM systems, and offline channels. MarketMuse AI-powered recommendations worked to optimise content, boost search rankings and enhance domain authority. MarketMuse was integrated with WordPress CMS to improve engagement metrics thanks to real-time content updates and metadata enrichment
• Gen AI-powered CDPs analyse enormous volumes of client data to deliver real-time, actionable insights. For instance, Einstein Predictive Lead Scoring ranked leads based on engagement, demographics, and purchase history. And it was a game changer for predictive analytics, allowing a more precise budget allocation and dynamic decision-making
• Brandwatch’s machine learning processed social media data and accurately analysed industry-specific trends

Complex challenges are related to data privacy and security. AI systems must follow strict data protection protocols. For instance, differential privacy, when dataset randomisation is applied to anonymise users and maintain data utility with minimal compromise. Enhanced Privacy and Unified Data Collaboration Platforms help marketers to merge and enhance first-party data with insights following the necessary privacy regulations.

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