5 areas to embed generative AI into your digital commerce strategy
By Zhivko Rusev, SVP Salesforce at Tryzens
Generative AI has become a trend in the public conversation since November 2022, following OpenAI’s largest technological breakthrough – ChatGPT. AI has become generative and more powerful than ever, with application in many use cases across variety of businesses and the digital commerce landscape in particular.
Excitement around AI has led to a sense of urgency among business executives to adopt emerging tools to automate and improve processes company-wide. According to Google research, 64% of business and technology leaders feel the need to adopt generative AI, yet just 4% feel that their organisations have the necessary skills to do so.
Clearly, there is a natural latency between the rapid rise and proliferation of generative AI tools and the ability of businesses to adapt, train, and hire to have these necessary skills to be successful in defining and executing an AI strategy.
The initial uptake in generative AI among marketing teams to create better copy has spread into all areas. Businesses are using it to generate images, audio, and even using it to create next-level personalisation functionality.
Data from Botco found that 69% of businesses have started to use generative AI for image creation, 58% for text creation, 50% for audio and voice, 37% for developing chatbots, and 36% for generating code.
The spread of AI is also reflected in analysis by Business of Fashion, which found that fashion, activewear, and retail companies are developing strategies to use AI in areas with the most immediate impact, such as hyper-personalised digital shopping experiences.
Generative AI has the potential to create an additional $400-660 billion in the retail and consumer packaged goods (CPG) industries, according to a McKinsey study, helping to automate key functions such as customer service, marketing and sales, and inventory and supply chain management.
This moment of low adoption presents a valuable opportunity for brands and retailers to get in front of the competition by integrating AI into their day-to-day processes and establish themselves early on as AI leaders.
Tryzens works with brands and retailers to embrace generative AI into their daily processes – from ChatGPT, Midjourney, and Scribe to Dall-E2 and GitHub Copilot. Whether you’re yet to integrate AI or figuring out the best ways to use it, here are 5 areas to embed generative AI into your digital commerce strategy.
Generative AI can be used to create highly personalised email marketing campaigns, with an increasing number of platforms already offering integrated AI capabilities. By analysing customer behaviour, preferences, and purchase history, AI algorithms can generate tailored email content.
In March 2023, Salesforce announced that it will be launching Einstein GPT – the world’s first generative AI for CRM, providing capabilities across every cloud platform within its ecosystem – including Commerce Cloud and Marketing Cloud. The Einstein GPT Trust Layer is Salesforce’s technological breakthrough that solves business leaders’ biggest concerns around data privacy.
It enables customers to integrate with OpenAI’s advanced AI data models or plug in external ones to process real-time data gathered from multiple sources in Salesforce Data Cloud, helping to power hyper-personalised email customer journeys, leading to improved open rates, click-through rates, and conversion rates.
Brands and retailers are using AI algorithms to analyse customer browsing and purchasing behaviour to provide highly personalised product recommendations for many years, but with generative AI these recommendations are far more effective and could improve cross-selling and upselling capabilities.
With better intelligence, businesses can maximise average order value, enhance the shopping experience, and increase revenue by encouraging customers to explore additional products that align with their interests and needs.
One of the areas where brands can find quick wins with generative AI is product descriptions. AI-driven content generation platforms can now analyse product data, specifications, and customer reviews to automatically generate detailed and engaging product descriptions.
Other platforms can create enhanced, multimedia-rich product pages that include images, videos, and interactive elements that highlight product features and benefits.
Salesforce’s Commerce GPT can produce enhanced product descriptions for both D2C and B2B (Commerce on Core) stores based on instructions provided via prompt in a chat interface.
Other platforms are heading in the same direction, such as Shopify with the launch of Shopify Magic – its AI tool designed for commerce that automatically generates product descriptions, in April 2023. And it’s not just commerce platforms. The product experience platform Akeneo launched new AI-powered capabilities that also include product description generation.
AI-powered product descriptions will help retailers streamline the content production process while ensuring consistency in product data across channels, as well as enable marketers to focus one elevating the overall shopping experience.
As mentioned already, the more data you feed generative AI, the more it learns and understands. Brands can apply this to maintain brand voice consistency across all digital commerce channels. With the help of generative AI, organisations can analyse existing brand content and communication style to generate a broad range of content (website content, marketing copy, social media posts, customer messaging) that aligns with the brand’s unique tone.
Generative AI can maintain a consistent brand voice through text and audio, helping to power both chatbots and voice assistants, so that the brand can engage with its customers 24/7 across devices and channels, enhancing brand recognition, trust, and loyalty.
Also in March 2023, Adobe Commerce launched Sensei GenAI, technology that can automatically generate brand-aware content, incorporating the brand’s tone of voice and style guidelines.
Interestingly, generative AI is making it possible for brands to move beyond the traditional single voice approach and speak with multiple voices, using distinct tones for each segment of its customers and most importantly fine tune it across different regions as well. Forbes identifies this as marking a huge shift and opportunity for brands to tailor their tone and language, differentiating themselves from those “acting and sounding like monoliths.”
Generative AI can be applied to enhance the overall customer experience by gaining deeper insights into customer behaviour and preferences. The advanced language models are capable of analysing vast amounts of data, including customer interactions, feedback, and historical transactions, to identify trends, patterns, and emerging customer needs.
This valuable data-driven intelligence enables businesses to make informed decisions regarding product offerings, marketing strategies, and user experience enhancements. By proactively addressing customer preferences and pain points, brands can create a more tailored and satisfying shopping experience, resulting in higher customer satisfaction and loyalty.
Around 75% of customers already believe that generative AI will “vastly improve their interactions with companies,” according to Forbes, while another 71% believe that it will make customer experiences more empathetic. So, customer expectations are already heightened by the possibilities. It’s on brands and retailers to deliver a more personalised and responsive experience.
How to approach your AI strategy and what are the key success metrics?
If you are a senior leader in your organisation and have been tasked to define an AI strategy but don’t know where to start, a great first step is to define what your KPIs are and think about how you can improve them with the help of generative AI technology. This will help you define a long-term vision and strategy of where your organisation must be heading to achieve the defined objectives. You need to be thinking about optimising these core areas of your business:
1. The sales process – using generative AI helps to collect all your data from each system, platform, and each sales representative and centralise it, analyse it, and provide you with meaningful insights into how to:
– Improve the conversion of your opportunities
– Generate quotes faster
– See where you are losing or winning against competitors
– Automate the most time-consuming tasks to improve the performance of your sales reps
– Ensure you are providing customers with the details they need to be able to make a quick decision and buy your products or services
– Improve the overall process
2. Customer service – the implementation of generative AI enables your customer service agents to be more productive and resolve customer cases faster through a 360-degree view of your customers. This includes having an automated summary of conversations and better recommendations for upselling and cross selling.
3. Marketing – leveraging generative AI helps your marketing team create better personalised journeys for your customers quicker and to ensure that they feel recognised across every channel. Teams can also use it to refine their marketing strategies and ad campaigns to boost audience reach and engagement metrics.
4. Product creation & service definition – generative AI is able to analyse customer feedback more efficiently to inform and optimise the process of creating new products or adjusting existing ones. Equally, it can be applied to optimise the definition of new services to help your business evolve.
5. Finance – generative AI enables finance teams to analyse data related to business operations. This analytical process is key in identifying opportunities for enhancing various aspects, such as the optimisation of cost of goods, suppliers, third-party services, and platforms. It’s also effective in streamlining these processes while fostering a data-driven approach to decision-making.
6. HR & operations – generative AI can be plugged into your systems to enhance hiring processes, streamline talent management, optimise workflows, and predict recruitment needs. By automating tasks such as resume analysis, and resource allocation, it reduces operational overheads. It could be enormously powerful by assisting in employee training and upskilling by personalising content to suit individual learning curves and needs. And it can provide insights into employee morale, predicting potential turnover and helping retain top talent.
7. Research & development – reduce the time from ideation to product launch, generative AI can analyse vast amounts of data from various sources to predict market trends, consumer needs, and potential roadblocks. By optimising simulations and modelling, it helps teams visualise product performance in various conditions and scenarios. This not only expedites the prototyping phase but also increases the likelihood of the final product’s success in the market Generative AI also plays a role in peer review analysis by identifying research gaps and proposing potential areas for innovation, contributing to the development of a forward-looking product pipeline.
We expect generative AI to become a core part of business operations of every organisation, enabling them to improve the efficiency of every aspect of their business. As an international digital commerce agency, Tryzens empowers large organisations and retailers to incorporate AI into day-to-day processes, accessing the broad spectrum of benefits from higher productivity to enhanced customer experience.
If generative AI is your next digital frontier, then connect with Tryzens.
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