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Artificial intelligence (AI) represents the most transformative innovation since the advent of the internet. The expansive array of AI initiatives reflects its potential to revolutionise business strategies profoundly.
While the thought of integrating AI might seem overwhelming, the right tech partner will make the reality much more manageable. Adopting AI can be straightforward with a step-by-step approach and a skilled team will empower businesses to unlock their full potential effortlessly.
Transformative solutions with AI
Before we dive into the marketers’ roadmap, let’s explore just a few ways AI offers transformative solutions that can significantly boost productivity and efficiency. AI can revolutionise the core operations of enterprise companies, paving the way for competitiveness and profitability.
AI-driven chatbots and virtual assistants, for example, streamline customer interactions by handling routine enquiries, freeing up human agents to tackle more complex issues. This not only accelerates response times but elevates customer satisfaction.
Another use case is using AI to analyse data from equipment sensors to enable predictions of potential failures or maintenance. This proactive maintenance approach minimises downtime and extends equipment lifespan. For example, if a new part is needed, SAP customer Miele Professional offers a speedy and efficient service with predictive AI helping sales and service teams react quickly to meet customer requirements.
AI algorithms enhance an organisation’s security by monitoring network activity for anomalies that may signal cyber threats, using historical data to identify risks swiftly and accurately. In supply chain management, AI improves planning by forecasting the best transportation routes, managing warehouse operations and predicting inventory needs, which collectively reduce costs, improving sustainability and delivery efficiency.
In human resources, AI streamlines the recruitment process by efficiently scanning through vast numbers of CVs to pinpoint suitable candidates and predict who is at risk of leaving. AI also automates routine financial tasks, enabling finance professionals to concentrate on strategic decision-making.
AI supports quick decision-making by analysing large data volumes in real-time, which is crucial in sectors like finance where rapid response to market changes is paramount. Another use case is AI’s predictive modelling capabilities, which can simulate new products, predict outcomes and refine designs before they reach the market, significantly reducing development cycles and improving innovation.
What does this mean for marketers?
In an era where consumer expectations are soaring, marketers face the daunting challenge of balancing tried-and-true strategies with innovative approaches.
This is where AI steps in.
Marketers quickly realise that without AI, the most creative campaigns lack the muscle to deliver significant business outcomes. With SAP Emarsys, for example, multilingual campaign production from marketing teams is expensive and getting together the necessary copy and content to speak to individual customer segments is hard.
Our focus is to improve the production cycle of campaigns from segment through to execution and analysis. AI tells you which customer groups are big, underserved opportunities and helps put together a campaign to target them. AI helps to send at the right time on the right channel. AI also allows you to, in natural language, ‘Just Ask’ how the campaign performed and integrates across Google Data and SAP Data (including Emarsys) to build campaign reports.
This helpful article on AI in marketing and sales from McKinsey & Company indicates that players that invest in AI see a revenue uplift of three to 15 percent and a sales ROI of 10 to 20 percent. The feature highlights how winning companies – those increasing their market share by at least 10 percent annually – exemplify the use of advanced sales technology.
These organisations typically build hybrid sales teams and capabilities, tailor strategies for both third-party and company-owned marketplaces, achieve e-commerce excellence across the entire funnel and deliver hyper-personalisation. This hyper-personalisation involves crafting unique messages for individual decision-makers based on their needs, profiles, behaviours and interactions – both past and predictive.
Similarly, our own SAP Emarsys research, specifically among marketers, underscores the efficiency AI brings. Nearly half of Australian marketers currently using AI (49 percent) say that it saves them between three and four hours launching a marketing campaign. Almost all marketers using it are saving at least an hour. The question is no longer if AI needs to be used but how it can be harnessed to amplify not just marketing but every area of the business.
Knowing these kinds of benefits are possible, an AI-infused marketing strategy is a must-have. Marketers in any industry who want to begin using AI to enhance campaigns, streamline processes and deliver better customer experiences – or take the next steps on your AI journey – here’s how to outpace the competition and turn the buzz into tangible results.
Start with GenAI tools for everyday marketing tasks
The biggest AI buzz has been around Generative AI (GenAI). Many of us have played around with tools like OpenAI’s Chat GPT, DALL-E or perhaps Midjourney. So, a logical first step is to incorporate GenAI marketing tools into everyday marketing workflows and tasks to make these easier and quicker. As a brief aside, if AI is completely new to you, this Demystifying AI guide is a great starting point and invaluable in explaining what it’s all about.
GenAI marketing tools draw on those increasingly familiar large language models or LLMs, like Chat GPT-4 to accelerate the content creation process and improve content relevancy by quickly generating text, images or summarising data. These tools can guide you in terms of better connecting with customers and help generate content that will resonate with them.
GenAI tools for subject lines, pre-header copy and campaign content blocks
The most straightforward GenAI tools are ones that help you generate subject lines, pre-header copy or blocks of content for marketing campaigns.
Subject line generators create context-specific email subject lines that consider language preferences and the level of creativity you’re after – all directly within an email editor.
Linked to this are AI pre-header generators that deliver engaging email preheaders. The text generated reflects the context of the email and the chosen subject line, user prompts and settings – invaluable in capturing your customers’ attention and increasing email opens.
Additionally, you can create marketing campaigns more quickly with an AI product finder tool that uses AI-assisted search to reduce the time it takes to find and insert specific products across marketing campaigns. We’re talking about reducing hours spent scrolling through product catalogues to seconds by using keywords and filters to search product catalogue fields and drop content into a template.
The next evolution here will be solutions that allow users to ‘talk’ to their product catalogues and find the best products for campaigns using natural language prompts, such as “show me top-selling shoes that are not on sale but have excess inventory”.
GenAI tools for segmenting audiences
Solutions like segment generators can be used to find new or better reach existing audiences by understanding and creating customer segments using natural language descriptions and queries.
For instance, marketers can use a segment generator to analyse existing customer segments and create summaries of segments in plain English for easy comprehension and searchability. Or they can discover new segments to target using straightforward prompts like “Show me customers under 30 who bought something last month and love red heels”.
Turbocharge activity with predictive AI tools for enhanced personalisation
Once you’re comfortable with GenAI tools it’s time to get on board with Predictive AI. Predictive AI in marketing has been around for a while, but with much less fanfare. This set of AI tools, powered by machine learning, can analyse historical data to predict future events, enabling marketers to create more personalised recommendations, make predictions on future customer behaviour and uncover deep insights hidden in your data to reveal business opportunities.
Predictive AI for product recommendations
Predictive AI offers many options to marketers that can help with identifying audiences, channel selection, campaign content and timing, as well as measurement. Predictive AI tools span AI segmentation capabilities such as purchase predictions and lifecycle predictions to measurement tools that predict likely product affinity. Two that should certainly be on the marketers’ radar are product recommendations and send time optimisation.
These recommendations can be optimised and fine-tuned using personalised algorithms or models based on the customer’s buying stage along with other business rules. The result is the ability to create personalised content recommendation blocks that can be used across email, web and in-app mobile campaigns.
AI-driven insights to measure and evaluate engagement and shape future strategies
A third stage in an AI roadmap for marketers would be advanced analytics and calculations. This involves leveraging AI to power sophisticated mathematical models that generate actionable engagement and performance insights – in other words, they tell you why customers are behaving in a certain way and what to do about it.
AI-driven analytics use historic metrics on customer revenue and purchases, such as average lifetime spend, current revenue and past purchasing data and add AI to help predict average future spend, likely revenue increase and product affinity.
These insights allow marketers to evaluate and compare the effectiveness of marketing strategies right down to specific promotional campaigns. ‘Smart Insight’ for example collects data across touchpoints and then uses advanced scoring models and predictive algorithms to convert all that data into actionable insights.
‘Smart Metrics’ allow marketers to compare and evaluate marketing performance and look at things like Predictive Revenue, which is AI-powered and can reveal predicted future revenue increases or predict the average future spend of a lead.
Marketers assemble! Here’s your AI-ready team
You have an outline of an AI adoption roadmap, but how do you assemble an AI-ready crew to embark on this journey? The good news is if you’re already an effective, capable marketing unit, you’ve likely got that team together already. AI empowers the marketer, but you don’t need an AI specialist on the team to leverage that power.
The marketing landscape has changed with AI. The skill set required of a successful marketer hasn’t. You still need marketers who are curious, creative, customer-obsessed, open to change, comfortable with new ways of working, data literate… the list goes on. Marketers have always had to wear many hats.
AI is just the latest hat. Stay results-driven, measuring marketing efforts with relevant KPIs and metrics. Transformational as it is, AI is simply the latest tool in your arsenal, enhancing your ability to deliver better customer experiences.
It’s the same story when it comes to measuring the success of AI-driven initiatives.
Of course, at a vendor level if you’re evaluating AI technology you need to consider whether your GenAI tools are accelerating time to value and making work tasks easier. Is your Predictive AI delivering enhanced customer experiences with real-time insights? Are you leveraging AI-powered analytics to reveal intelligent insights that enable true lifecycle marketing? And so on.
Otherwise, at a campaign level, the same smart KPIs and metrics you’d use for any marketing initiatives apply.
Relevant, reliable and responsible AI
For us, AI is not a new, shiny or scary thing. It’s part of our heritage. We’ve been working with AI and embedding its predictive capabilities into our systems for more than a decade. Back in 2018, SAP first established its Guiding Principles for Artificial Intelligence.
We build our AI systems with three core principles in mind. The first is relevancy. Each of our AI features and tools is embedded purposefully into marketing workflows. In other words – it’s about real solutions that bring power to the marketer.
The second is reliability – that means training AI on the industry’s broadest business datasets and building on a scalable and secure foundation. And third, is responsibility – deploying AI that is built on the highest ethics and data privacy standards.
Relevant, reliable and responsible AI are our watchwords. With those three core principles as our guide, we leverage AI in our solution to bring more power to marketers, enabling them to build, launch and scale AI-powered personalised omnichannel engagements that deliver business outcomes.
Thomas Harris is the chief revenue officer at SAP Emarsys. For more than 10 years, Harris has scaled high-performing teams from a regional to a global level. He has a proven track record of driving triple-digit growth and supporting leading global brands to realise their greatest personalisation and omnichannel aspirations.
Also, read the other two parts of Harris’ Marketing Mag exclusive three part series on AI.
Part one: AI isn’t about automating tasks, it’s about transforming them.
Part two: An extensive guide on the future of AI in marketing.
