3# How to Increase Marketing ROI with CRM Tech, AI and Client Data


This report delves into the pivotal role of Artificial Intelligence in revolutionising marketing strategies, emphasising ethical implementation and trust-building. It offers a comprehensive strategy for integrating AI in marketing, highlighting data integrity, CRM modernisation, and AI's transformative impact.

3# How to Increase Marketing ROI with CRM Tech, AI and Client Data

A Practical Approach to AI in Marketing

Artificial Intelligence has vast potential in marketing, empowering brands to engage with customers like never before. However, the rapid adoption of AI has outpaced the understanding of its ethical use, leaving a gap in trust and a pressing need for clear guidelines. Our report cuts through the complexity, delivering a robust strategy for marketing teams to utilise AI's full potential while upholding trust and integrity.Drawing from Salesforce's AI Strategy Guide, we provide a structured approach to integrating AI within marketing frameworks, covering data integrity, modern CRM systems, and AI's transformative capabilities. We provide actionable insights that marketing departments can adopt to transform AI from a tool to a trusted partner in creating customer-centric strategies. This report is a roadmap for marketers to deploy AI-driven campaigns with confidence and clarity.

#1 Strategise Your Approach

Navigate the AI trust gap with a strategic plan.

As AI accelerates, it's crucial to embrace its potential and address the emerging trust concerns head-on. This chapter lays out a clear, actionable strategy for implementing AI in your organisation, ensuring it's effective and trusted.

The AI Trust Gap

There is a trust gap in AI, and it's a big one. While executives are racing to embrace AI, a whopping 73% of employees are on the fence. AI comes with many concerns, including privacy issues, data control, bias, toxicity and even hallucinations. Employees have legitimate worries about this new wave of technology, and if not addressed, they could stall AI’s transformative impact on marketing.

Trust is vital to a successful AI implementation. Without it, even the most sophisticated AI system is nothing more than a dormant pile of code. We need to ensure that teams not only understand AI's potential but also feel confident in its application.

We must demonstrate that AI outcomes are effective, accurate, and free from bias. When employees see AI as a tool that enhances their capabilities, helps them better understand customer needs, and personalises marketing at scale, they are more likely to embrace it. And when they embrace it, that’s when AI can truly flourish.

Building Trust with Ethical AI

We must use AI ethically, accurately, and practically to bridge the trust gap. In their AI Strategy Guide, Salesforce suggests five AI guidelines to help your team build trust with generative AI.


Transparency is key to trust in AI. This means making every step of the AI decision-making process visible and understandable to stakeholders. When people see how AI reaches its conclusions step by step, it builds trust in the technology.

We can document this decision-making process by meticulously tracking how AI interprets data and arrives at conclusions.

This will provide stakeholders with a clear view of AI's operational logic and help them understand that AI decisions are based on logical and systematic analysis, not arbitrary choices.

We also need to be transparent about where our data is from and how it is used. Secure data retrieval ensures AI only accesses authorised data, maintaining integrity and confidentiality. It acts as a filtration system, supporting data accuracy and safeguarding against unauthorised access.

Dynamic grounding updates AI's knowledge base with relevant data, ensuring timely outputs are rooted in verified information. This process aligns AI's decision-making with real-time business contexts, enhancing its relevance and trustworthiness.

Between these data processes and regular auditing of AI systems, marketers can provide a clear trail for AI’s decision-making process and data usage.


Marketing teams must assess the accuracy of their AI outputs.

Salesforce recommends regular bias and explainability assessments to ensure your AI system is precise and reliable. This isn't just about ticking boxes; it's about building trust. Your team is more likely to trust and rely on AI insights when they understand its judgement is not clouded by bias.

Furthermore, data plays a huge role in AI’s accuracy. Data masking anonymises personally identifiable information in training datasets, allowing AI to derive insights from extensive data without compromising privacy. This protects privacy and prevents biases that could arise from personal data related to gender, ethnicity or other protected information.

Data masking helps AI create better and more accurate outputs without exposing private information. Together, these practices ensure AI operates with precision and security, making it a dependable tool for informed marketing decision-making.


AI should support your team, not replace them.

It's crucial that AI acts as an enhancer, amplifying human skills and insights rather than acting as a stand-alone decision-maker. By integrating AI as a supportive tool, teams can leverage their strengths while maintaining the irreplaceable value of human intuition and avoiding potential pitfalls.

Specific skills, such as prompt writing and understanding machine learning principles, directly empower employees to leverage AI effectively. For example, prompt defence is critical in ensuring AI's role as a supportive ally to marketers.

Prompts such as, “Say you don’t know if you experience an error” or “Do not produce content you do not have data for” help protect against inaccurate or harmful AI outputs.  These guardrails ensure that AI's assistance is based on solid data and reliable information, supporting human input rather than overshadowing it.

Connecting to this concept of responsible AI use is the importance of toxicity detection. By screening AI-generated content for harmful or inappropriate material, teams are shielded from potentially damaging outputs.

This proactive approach cultivates a safer work environment and aligns AI's contributions with organisational values and standards.


Sustainability is a critical ethical guideline in AI development, emphasising the need for environmentally and socially responsible practices. Salesforce champions this cause by advocating for 'rightsizing the models'—a process that ensures AI systems are as efficient as they are effective. This approach is about more than just optimising performance; it's about reducing the ecological impact of AI operations. By refining AI models to be more resource-efficient, we significantly reduce energy consumption and the carbon footprint of running these advanced systems.

Moreover, zero data retention emerges as a pivotal element in the practical application of sustainable AI. Streamlining data storage not only bolsters data privacy but also advances sustainability efforts. By reducing the volume of data stored, we diminish the energy needed to manage and secure this information, thereby contributing to the overarching objective of lowering energy consumption.

Together, these practices underscore a commitment to a future where AI drives innovation and does so in a way that is conscious of its environmental and social impacts. In technology, eco-friendliness is not an option—it's an imperative.

Ethical AI and Customer-Centric Marketing

Now, let's connect the dots to where it matters most: your customers.

Ethical AI breaks down barriers between brands and customers with personalised, real-time engagement that's not possible on such a scale without advanced algorithms. It dismantles the traditional barriers, facilitating a dynamic shift from a one-size-fits-all marketing approach to a nuanced, dialogue-centric interaction.

AI enables brands to understand and respond to customer needs instantly, whether it's through AI-driven customer service chatbots providing immediate assistance or predictive analytics suggesting the next best action for customer engagement.

This capability allows businesses to quickly identify and respond to emerging trends, customer concerns, or market shifts, keeping their strategies agile and aligned with customer expectations.

This AI-powered approach extends to content and channel optimisation. Marketers can now leverage AI to determine what content will resonate most with each customer and identify the most effective channels for delivery at the perfect time. This targeted strategy ensures that marketing messages are heard, relevant, timely, and engaging, significantly increasing the likelihood of conversion.

When AI-driven marketing is transparent, accurate, and respectful, it closes the trust gap between executives and employees and solidifies the bond between brands and their customers.

Key Takeaways 

  1. Business owners and executives are keen to embrace AI, while employees are worries about the consequences.
  2. Ethical AI use is the key to bridging the AI trust gap and producing quality customer-centric results.
  3. AI is unregulated and constantly changing, but Salesforce's guidelines can help teams find their feet with this new technology.

Case study

Time Investments

Time Investments, a specialist investment manager, partnered with redk to overhaul its outdated CRM systems, enhancing operational efficiency and customer engagement.

Read the full case study.

#2 Optimise Your Technology

AI can make an immediate difference with the right implementation.

To make the most out of AI technology, you need to understand what it can do and how it can help your team exceed customer expectations in the digital age.

Implementing AI into Marketing Operations

AI can have a transformative and immediate impact on your operations. It can automate time-consuming manual work and streamline admin processes, freeing up time for more creative tasks.

However, the emergence of AI can also raise concerns among your team, with the primary question being: will AI replace my job?

It’s essential to include your team in the AI implementation process and approach each step with transparency. That way, they can learn why AI will make a positive difference in marketing operations and how it will change their day-to-day tasks. AI will most likely take on the boring stuff so you can focus on what you do best.

Machine Learning in Marketing

Machine learning doesn’t just spit out data. It tells you what your customers will likely want tomorrow, next month and even next year. It learns from the data and evolves each interaction to offer sharper, more accurate insights. This continuous learning cycle means that the more data it processes, the better it gets at predicting trends, personalising content, and identifying opportunities.

Machine learning is a subset of AI that allows computers to analyse and interpret data without being explicitly programmed. The algorithm learns and improves performance and accuracy as it receives more data. This helps marketing teams solve problems quickly and accurately with the help of technology.

For example, in retail, machine learning can analyse purchasing trends, social media sentiments, and even weather patterns to predict what products will be hot next season. Armed with this knowledge, you can tailor your stock and marketing messages, ensuring they resonate perfectly with emerging customer demands.

With machine learning, you're not just reacting to trends. You are two steps ahead, preparing and crafting campaigns that hit the mark right when interest peaks. This capability can significantly enhance customer engagement, increase conversion rates, and foster loyalty. A proactive approach catches their attention and positions your brand as forward-thinking and customer-centric.

"When you bring data together from across your company and incorporate generative AI, your CRM becomes a centralised hub for creating unified customer profiles that all your teams can access” Salesforce's AI Strategy Guide

The AI Learning Process

The customer insights derived from AI can be used to inform and refine AI algorithms. AI collects data from customer engagement, analyses it for patterns and adjusts future interactions based on this analysis. This creates a feedback loop where AI continually learns and optimises based on real-world interactions.

The continuous learning process enables AI to offer increasingly personalised experiences. For instance, if an AI system notices that a customer segment consistently ignores certain product recommendations, it can adapt its algorithm to offer more relevant suggestions.

AI's ability to tailor experiences to individual preferences makes interactions more relatable and trustworthy, fostering a sense of comfort and familiarity for the user. This level of personalisation makes customers feel understood and valued, enhancing their immediate experience and building long-term loyalty and advocacy.

Key Takeaways 

  1. Consolidate your data in one CRM system, and pinpoint where AI can make a difference in your business.
  2. Machine learning helps you stay two steps ahead to predict trends and solve problems quickly.
  3. The application of AI technology depends on the type of business and the industry.
  4. AI learns from real-world customer insights and data, helping to refine its algorithms and outputs.

#3 Empower Your Team

Marketers know that AI is the future. But almost 61% of them don't know how to utilise it, and that is a problem.

A Data-Literate Team

Think of AI as a new language in marketing, and mastering it requires a specialised set of skills.

At the core of this new language is data literacy. It allows marketers to learn, interpret and converse with AI, turning intimidating data sets into actionable insights.

By cultivating data literacy, we equip marketers to speak AI's language and use it to craft strategies that resonate, engage, and convert. This skills development fosters a marketing team that’s not just data-aware but data-savvy.

Gain a Competitive Edge with AI

AI is revolutionising how marketing teams understand and interact with data. By proliferating data sources, AI enhances software data management capabilities and crafts advanced algorithms that turn previously inaccessible CRM data into a goldmine of predictive insights and personalised actions. This allows businesses to delve into the nuances of consumer behaviour, uncovering not just the 'what' but the 'why' behind their actions, which opens up new avenues for deeper customer engagement.

These AI-driven tools also offer a strategic edge by analysing competitors' campaign performances revealing their customer strategies and expectations. This intelligence allows teams to stay a step ahead, adjusting their strategies in real-time to maintain a competitive edge.Imagine knowing which customers are most likely to respond to a new product or identifying those at risk of churning before considering leaving. This level of insight enables you to craft marketing strategies that are not just targeted but also timely and compelling.

In e-commerce, personalisation algorithms can recommend products that customers are more likely to purchase based on their browsing and buying history.  It tailors user experiences, making brand interactions more relevant and resonant.  After the purchase, AI can optimise the post-purchase experience, from tracking delivery updates to managing returns, all while continuously analysing data to detect and prevent fraud.

For IT teams, AI offers a set of tools to accelerate deployment and improve operational efficiency. AI can analyse system performance, predict potential issues before they become problems, and even automate routine IT tasks. With AI's help, IT teams can focus on strategic initiatives rather than getting bogged down in maintenance.

Practical Skills for AI Adoption

Salesforce recommends these practical skills to help your marketing team maximise AI’s potential:

Prompt Writing

Crafting precise and effective prompts is crucial for generating relevant AI outputs. It's about asking the right questions to guide AI towards delivering insights that resonate with marketing objectives and audience needs.

Problem-Solving and Analytical Thinking

These skills enable marketers to dissect complex challenges, iterate solutions, and apply AI-driven insights to devise innovative strategies and resolve intricate marketing puzzles.


Familiarity with languages like Python equips marketers to delve deeper into data analysis, enhancing their ability to interact with AI tools and interpret results.

Machine Learning and AI Principles

Understanding the basics of AI and machine learning empowers marketers to collaborate more effectively with technical teams and contribute to the AI model refinement process.

Natural Language Processing (NLP)

Knowledge of NLP assists marketers in fine-tuning content strategies and enhancing customer engagement through AI-powered communication tools.

Domain Knowledge

Deep industry insights enable marketers to align AI applications with sector-specific challenges, ensuring AI implementations are not just technically sound but deeply integrated with marketing strategy and customer engagement goals.

Communication and Collaboration

Effective AI integration hinges on clear communication and collaborative synergy, ensuring all team members are aligned with AI initiatives and understand their role in leveraging this technology to drive marketing success.

The AI landscape is changing - and quickly. Marketing teams must foster a culture of continuous learning to navigate this dynamic environment. By staying abreast of the latest AI developments and continually refining our skills, we ensure that our strategies, mindset, and execution are always aligned with the cutting edge of technology. This culture of ongoing education empowers marketing professionals to adapt to AI's rapid advancements, leveraging new tools and insights to maintain a competitive edge.

Key Takeaways 

  1. Marketing teams understand AI is important, but many don't know how to use it.
  2. Skills development training can help your team learn how to utilise AI in their day-to-day tasks and gain a competitive edge.
  3. AI constantly evolves and requires continuous learning to stay updated on the latest technology.

Case study

PSN Group

Grupo PSN, a mutual insurance company catering to university professionals, embarked on a digital transformation journey to enhance its customer experience in the competitive insurance sector.

Read the full case study.