Investing in generative AI: how to maximise the customer experience

31 de October de 2023

Generative artificial intelligence is emerging as a transformative force in sales and marketing, driving personalisation and efficiency. As consumer expectations evolve towards richer and more accessible experiences, businesses are looking to generative AI as a vital tool to innovate and stay competitive. This approach offers not only strategic advantages but also significant challenges, setting the pace for the technological investment and adaptation needed for the future.

Why invest in generative artificial intelligence?

The opportunities and risks of generative artificial intelligence “promise to alter the way B2B and B2C players think about customer experience, productivity and growth.”

According to a McKinsey article, omnichannel is at an inflection point where companies must adapt to meet changing customer demands. Customers are looking for access to everything, everywhere, all the time. While they still value the combination of on and off channels, there is a growing preference for ecommerce and new ways of shopping.

Leading companies, those that manage to increase their market share by at least 10% annually, tend to employ AI techniques and advanced technology in their sales strategy. They also build hybrid sales teams and capabilities, adapt their strategies to embrace new markets, pursue excellence throughout the sales funnel and offer extreme personalisation. This means tailoring communications to the customer based on their needs, habits, behaviour and past and future interactions.

AI technology is constantly evolving, becoming more accessible and affordable to implement. In this article, McKinsey estimates that approximately 20% of current sales force functions could be automated.

Investment in generative artificial intelligence

Investment in AI by venture capitalists has increased 13-fold in the last decade, leading to an exponential increase in the availability of “usable” data and accessible technology. We now have vast amounts of data available to train base models, and since 2012 computational capacity has increased a million-fold, doubling every three to four months.

According to the consultancy, leading companies are prioritising the implementation of this technology to achieve this:

  • There is a clearly defined AI vision and strategy.
  • More than 20% of digital budgets are invested in AI-related technologies.
  • Teams of data scientists are employed to execute agile pricing strategies and optimise marketing and sales.
  • Strategists are looking to the future and describing generative AI use cases.

In addition, collaboration between marketing and sales, customer experience (CX) and content marketing are top priorities for advertisers and agencies as revealed by the Spanish Marketing Association (AMKT) in the study “Marketing Hot Trends 2023”.

  • Investment in these fields is expected to increase, with 71% of companies looking to improve CX.
  • Artificial Intelligence and machine learning are of particular interest, with 48% of companies planning to increase their spending in these areas.

AI is already used in almost half of marketing departments, especially in small businesses, for content creation and adaptation, although adoption varies by company size and specific application.

However, they also note that when business leaders in these companies were asked about the barriers limiting the adoption of AI technologies in their organisation, internal and external risks topped the list.

From intellectual property infringement to data privacy and security, these risks require thoughtful data governance strategies, which may well require the creation of new roles and capabilities to make the most of the opportunities ahead.

What are the keys to a secure investment?

The consultancy has compiled a series of actions to initiate an AI transformation in sales and marketing:

  • Conduct a business audit: Assess your technology infrastructure and the skills of your marketing and sales teams; explore partnerships with technology players that can help you implement generative AI use cases.
  • Create an AI task force: Create a cross-functional team (including, for example, members from marketing, sales, pricing and IT) to explore AI opportunities and test the applicability of use cases.
  • Identify quick opportunities in your customer journey: Look for simple, high-impact, low-cost, low-risk use cases (such as prospecting email automation) and set boundaries to reduce risk.
  • Experiment with Generative AI: Test use cases in a specific part of the sales funnel, study the results, and refine for larger scale deployment.
  • Train your teams in generative AI: Train your sales team in generative AI so they have a better understanding of potential applications and the confidence to start experimenting.
  • Set security rules: Prohibit the introduction of sensitive customer data into generative AI tools and set high standards for verifying results.

Do you know CognoIA?

At Cognodata, we have built an artificial intelligence accelerator platform based on advanced analytics, machine learning and generative AI. It allows us to streamline execution and inject our expertise into the projects we undertake.

Through this platform, we seek to accelerate the development of analytical models and facilitate the application of generative intelligence for the application of new use cases and the improvement of our clients’ processes and services.

“CognoIA applies artificial intelligence and data science to improve business processes and boost our clients’ results”.

We also participate in the Microsoft partnership programme. In which we seek the development of models within the Azure OpenAI environment and the joint research of new use cases for the application of ChatGPT, Codex and DALL-E in private environments. In this way, we seek to offer all the security and data protection guarantees that we currently offer our customers (ISO 27001, 27701, UNE-19601, PCI-DSS).