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Your quick guide to AI marketing stacks – what are the most popular use cases and best solutions?


With new AI marketing solutions coming out daily, where do you start, how do you asses what are the emperor’s new clothes to those genuinely game changing solutions?

 

To help your own assessment, we’ve broken it down by:

-what are the most popular use cases for AI in your marketing efforts

-most popular AI solutions for those use cases

-to balance out any fears of AI, why AI won’t be replacing marketeers.

 

 

Lets start with the ten most popular marketers’ use cases (according to ChatGPT)

 

1.Customer insights and segmentation

 

AI can analyse customer data from various sources to identify patterns, preferences, and behaviours. This information helps marketers create more targeted campaigns and personalized messaging.

 

2. Content creation and optimisation

 

AI-powered tools can generate and optimise content at scale. This includes writing product descriptions, blog posts, social media updates, and even generating video content.

 

3. Personalisation

 

AI enables marketers to deliver personalized experiences to customers in real-time. This could be through personalized product recommendations, tailored email marketing, or dynamically generated website content.

 

4. Predictive analytics

 

By analysing historical data, AI can predict future trends, customer behaviours, and potential outcomes. This helps marketers make more informed decisions about where to allocate resources and which strategies are likely to be most effective.

 

5. Chatbots and virtual assistants

 

AI-powered chatbots and virtual assistants can handle customer inquiries, provide support, and even assist with purchases. They can offer 24/7 assistance, improving customer satisfaction and reducing response times.

 

6. Ad-targeting and optimisation

 

AI algorithms can analyse user behaviour and preferences to optimize ad targeting across various channels. This maximizes ad performance and ensures that marketing budgets are used efficiently.

 

7.Customer Service and Support

 

AI can analyse customer inquiries and provide automated responses or route inquiries to the appropriate department. This streamlines customer service processes and improves response times.

 

8. Voice Search Optimization

 

With the rise of voice search, AI helps marketers optimize their content for voice-based queries and understand the nuances of natural language processing.

 

9.Social Media Monitoring and Sentiment Analysis

 

AI tools can monitor social media channels in real-time, analysing conversations and sentiment around a brand or product. This helps marketers understand public perception and respond appropriately.

 

10.Sales Forecasting and Lead Scoring:

 

AI can analyse sales data and customer interactions to forecast future sales and identify the most promising leads. This enables sales teams to prioritize their efforts effectively.

 

 

As the old saying goes, ‘no one got fired for buying IBM’ – so let’s stick to the tried and tested:

 

  1. HubSpot: HubSpot offers a suite of AI-powered tools for marketing, sales, and customer service. It includes features like lead scoring, email marketing automation, content management, and CRM integration.

  2. Adobe Sensei: Adobe Sensei is an AI and machine learning platform integrated into various Adobe products such as Adobe Marketing Cloud and Adobe Creative Cloud. It provides features like image recognition, content personalization, and predictive analytics.

  3. Salesforce Einstein: Salesforce Einstein is an AI-powered CRM platform that helps businesses automate tasks, personalize customer experiences, and make data-driven decisions. It includes features like lead scoring, predictive analytics, and automated email campaigns.

  4. Google Marketing Platform: Google offers several AI-powered tools for marketing, including Google Ads, Google Analytics, and Google Optimize. These tools help marketers optimize ad campaigns, analyse website traffic, and conduct A/B testing.

  5. IBM Watson Marketing: IBM Watson Marketing provides AI-powered solutions for customer segmentation, personalized marketing campaigns, and customer journey analysis. It includes features like predictive analytics, sentiment analysis, and chatbot integration.

  6. Sprinklr: Sprinklr is a social media management platform that uses AI to help businesses manage their social media presence, engage with customers, and analyse social media performance. It includes features like social listening, sentiment analysis, and influencer identification.

  7. Optimizely: Optimizely is an experimentation platform that uses AI to help businesses optimize their websites and mobile apps. It includes features like A/B testing, multivariate testing, and personalization.

  8. Conversica: Conversica is an AI-powered virtual assistant for sales and marketing that engages with leads via email and SMS. It helps businesses qualify leads, schedule appointments, and follow up with prospects automatically.

  9. SAS Customer Intelligence: SAS Customer Intelligence is a suite of AI-powered marketing analytics tools that help businesses analyse customer data, predict customer behavior, and personalize marketing campaigns. It includes features like customer segmentation, campaign optimization, and recommendation engines.

  10. Cognizant TruMingle: TruMingle is an AI-driven customer data platform (CDP) that helps businesses collect, unify, and activate customer data across multiple channels. It includes features like data integration, identity resolution, and real-time personalization.

 

 

Marketeers will be here for a while yet, why?

 

  1. Creativity: AI is excellent at processing data and generating insights, but it lacks human creativity. Marketers are essential for coming up with innovative ideas, crafting compelling stories, and designing engaging campaigns that resonate with audiences.

  2. Emotional Intelligence: Marketing often involves understanding human emotions, motivations, and cultural nuances. AI may struggle to interpret complex emotions or adapt to rapidly changing cultural trends in the same way humans can.

  3. Strategy and Planning: While AI can provide data-driven insights and recommendations, it's up to marketers to develop overarching strategies, set goals, and make critical decisions based on broader business objectives.

  4. Relationship Building: Marketing is not just about transactions; it's also about building relationships with customers. Human marketers excel at building trust, empathy, and rapport, which are essential for long-term customer loyalty.

  5. Adaptability and Context: AI operates based on predefined algorithms and data inputs. Human marketers can adapt to unexpected situations, respond to feedback, and understand the broader context of a marketing campaign in ways that AI cannot.

  6. Ethical Considerations: AI algorithms are only as good as the data they are trained on, and they can perpetuate biases present in that data. Human marketers are responsible for ensuring that marketing strategies are ethical, inclusive, and aligned with the values of the brand and its customers.

 

Still not made your mind up?

 

Here are some additional places of support.

 

The AI Marketing Stacks – series of videos:

 

 

22 best AI marketing tools for 2024

 

 

Forbes – what marketeers should consider when thinking of applying AI.

 

 

 

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