Artificial intelligence (AI) has the power to transform marketing by helping marketers increase their reach, improve the effectiveness of campaigns, increase customer satisfaction and loyalty, generate more sales and boost profit margins.
Within the context of B2B marketing, AI refers to using software and algorithms to make automated decisions based on data collected about customers, prospects and other audiences of interest. In particular, AI-driven tools can efficiently and accurately mine large data sets for trends and patterns that human marketers might miss. AI can also enable real-time ad personalisation at scale, automate media buying, improve the speed and reliability of decision making, and even drive automatic content generation. In most cases, AI is supporting and augmenting the work of human marketing teams (and is still a very long way from being powerful enough to manage major marketing activities independently).
In today’s blog post, we explore how AI can be used in every aspect of your life sciences marketing strategy, from advertising and analytics, through to content marketing, social media, email marketing, customer service, and more, looking at how AI can provide benefits across all areas of your marketing operations.
And, as a quick demonstration of what is currently possible, the header image for this blog post was created in 30 seconds using Open AI's DALLE-2 automated image generation tool!
- Artificial intelligence or just automation?
- How AI can help with marketing analytics and data analysis
- Using AI in life science advertising and paid media campaigns
- Content Marketing and AI in the life science sector
- AI to help drive better life science email marketing
- Life science social media marketing and AI
- Using AI to improve life science SEO
- The benefits of AI for life science eCommerce
- The future impact of AI on life science marketing
Artificial intelligence or just automation?
How powerful are today’s current marketing AI tools? Have we reached the point where AI is driving truly intelligent actions and decisions? Or does the AI still require a significant level of human oversight (with the AI effectively just automating steps defined by human input)?
To help answer these questions, Paul Roetzer and Mike Kaput provided a handy scale as part of their recent book, "Marketing Artificial Intelligence". They use 5 levels to describe the independence of a given marketing AI tool:
- Level 0: All marketer (no AI, all automation is based on rules input manually by humans)
- Level 1: Mostly marketer (some intelligent automation, but still mostly driven by human inputs and oversight)
- Level 2: Half human, half machine (the AI system can manage some aspects but still requires input from a human)
- Level 3: Mostly machine (the system can operate independently of human controls and input in some cases, but others still require some sort of human input)
- Level 4: All Machine (the system is capable of functioning at or above human level without requiring oversight from a marketer, who simply defines the desired outcomes, and then the machine delivers them)
As Roetzer and Kaput say, "Much of the marketing technology you use today is Level 0: all human, all the time."
"The software does not learn, it does not improve, and it does not make you better at your job. Most AI-powered marketing solutions on the market today ... fit into Levels 1 or 2. Level 3 is possible but likely only after a significant investment of time and input during planning, training, and onboarding phases. Level 4 does not exist in marketing today."
So, with expectations suitably managed, let's look at how AI is impacting the work of life science marketers (and for a deep dive on the topic of marketing AI, we recommend checking out Roetzer and Kaput's excellent book on this topic).
How AI can help with marketing analytics and data analysis
The most advanced marketing analytics tools currently on the market use AI to intelligently organise and analyse data from a variety of sources, pulling out key trends and insights, as well as making predictions about the future. The insights generated can help you to optimise your marketing campaigns, website content, social media strategy, email copy and more. Common use cases include:
- Identifying which campaigns perform best and then using this intel to predict future performance
- Customising which messages and content people see based on previous behaviour
- Better scoring leads on how likely they are to purchase
- Keeping track of wider changes in the market, such as the activities of your competitors.
AI-driven analytics tools really excel when it comes to analysing extremely large datasets to pull out patterns and connections that humans would likely miss. As such, the life science companies most likely to benefit from AI-supported analytics packages are those with access to lots of data about their customers, prospects, website visitors etc. (especially those companies that have so much data that they become overwhelmed by the thought of manual curation and analysis).
One tool that you might find interesting in this area is Crayon, which is a competitive intelligence system. According to the company’s website, Crayon offers “a more informed picture of what your rivals are up to, with more than 100 different data types across millions of sources—including your team in the field.” The tool keeps track of competitor movements, including changes to their products, messaging, executive team and more, separating noise from genuine intelligence that you can use to hone your marketing efforts.
Using AI in life science advertising and paid media campaigns
When it comes to life science advertising, marketing AI can help you create your ads, improve their targeting and measure their effectiveness.
Firstly, AI can be used to create advertising content that's more personalised for each prospect. For example, if you know what a prospect is interested in (e.g. based on pages they have visited on your site or emails they have clicked on in the past), you can tailor an ad campaign specifically for this individual. This type of personalised marketing increases engagement because it feels less generic and is more tailored toward specific needs and interests.
Thanks to AI-based systems, it is also possible for you to deliver this level of ad personalisation at scale. By leveraging data on the performance of past campaigns, some tools can even predict the success of future campaigns, messaging and creative, before the ads are even deployed. As an example, Albert is a tool that automatically runs and optimises paid advertising campaigns. Albert plugs into your current ad tech stack and evaluates campaigns across Google, Facebook, Instagram, YouTube, and Bing, allowing it to make recommendations on improving performance.
Content Marketing and AI in the life science sector
High-quality content is the fuel of modern marketing. However, content can be time-consuming to create and there are no guarantees that what you publish will resonate with your target audiences and drive success for your team and business.
AI can help, by enabling you to create better content driven by relevant data and insights about the needs and interests of your audiences. AI can also help you to discover new topics that might be relevant for your business or industry, all of which helps to save you time and effort and gives you greater confidence that the content you produce will attract the interest (and attention) of your readers.
Another area where AI is really starting to impact content marketing is content creation and optimisation. Thanks to natural language generation models like GPT-3, machines are getting better and better at writing copy (although a lot of human oversight and intervention is still required to ensure the content is accurate, easy to read, and adds unique value to the reader). Meanwhile, other tools make it possible to generate world-class email subject lines based on evidence of previous success, all with the click of a button. Thanks to these tools, it is now easier than ever for you to create quality content at scale, while also providing you and your writers with creative prompts to help you overcome writer's block or come up with new copy variants to try.
With access to tools like GPT-3, we may be rapidly entering a future where writers spend as much time editing and reviewing computer-generated content as they do actually writing it themselves from scratch... but based on our experience, most of these tools are best used as a creative muse (with the writer still doing the majority of the heavy lifting when it comes to writing high-quality copy).
AI to help drive better life science email marketing
AI systems are already starting to help life science marketers get better results from email marketing by improving targeting and helping marketers create personalised emails at scale.
Let's start with creating better, more personalised content. With AI tools, you can analyse past data about your customers and create targeted emails based on their specific needs and interests. In other words, instead of sending all customers the same email every month (which could result in low open rates), you would send relevant emails only to those who have expressed interest in similar topics before. The more advanced AI tools can insert smart content into emails based on previous user behaviour (Rasa.io, the smart newsletter tool, is one such example).
In order to be able to send personalised emails, you also need to be able to track, segment and target people based on an understanding of what your audiences are looking for. From this perspective, you can also use AI to cleanse and enrich your customer data over time, while pulling on information and insights from across multiple sources to gain a deeper understanding of your target audiences. This helps to ensure your email marketing strategy is driven by a wealth of high-quality insights on each person.
By using AI-driven tools to send the right email, to the right person, at the right time, you'll be able to convert more prospects into customers with less time and effort... especially when working at scale.
Life science social media marketing and AI
Social media is a great place to make use of AI, as you can use it to detect consumer trends, monitor audience behaviour, create content at scale and better analyse campaign performance to drive future planning.
First, let’s look at how AI can help detect customer trends and audience behaviour across social media channels, including finding B2B influencers to partner with. You can use AI to identify key topics, events and trends within your industry or niche. This will help you quickly identify what topics people are interested in, so that you can create content around them all with increased confidence that your social posts will attract attention and engagement. You can also use AI to find the influencers to help further increase your reach.
By using AI to track audience trends and find influencers, you'll have plenty of data-driven insights to help fuel content production and distribution. But how can you generate this content at scale? AI can also help here, in a similar way to how companies are already using natural language generators like GPT-3 to produce content automatically based on topics and keywords provided by human users. There are also a range of other clever tools such as Lately, which can analyse the interests of your audience and repurpose your existing content into snippets to share on social media.
Finally, you can also use AI to track the performance of your social media campaigns and provide predictions for how future campaigns might perform. Whether or not AI can help you predict which posts will go viral (and which won't) remains to be seen, but there are certainly a growing number of tools that can help you to improve and scale your social media efforts.
Using AI to improve life science SEO
Search Engine Optimisation (SEO) is a good example of a marketing process that can be automated with AI. SEO is already a highly automated, measurable, repeatable process, making it an ideal candidate for smart automation by AI. Current AI-powered SEO solutions are already making it possible to conduct predictive keyword research at scale, analyse your existing website for opportunities and gaps, and even execute copy updates for you using natural language generators.
One example tool in this space is MarketMuse, which is an automated content inventory and audit solution that measures the quality, quantity, and authority of your content and provides insights on where you can improve your SEO strategy. Using the tool, you can research, organise, and prioritise your best SEO opportunities, allowing you to rapidly increase your rankings on search engine results pages with less effort.
The benefits of AI for life science eCommerce
While eCommerce is not prevalent in every vertical of the life science sector, it still plays a big role in areas such as reagents, chemicals and consumables. eCommerce marketers in such areas can likely leverage a lot of what we have already covered in this blog post to help analyse customer trends and create content at scale. However, there are a few areas where AI is having an additional impact on eCommerce, including product recommendations, customer service at scale, demand forecasting and more.
Let's begin by looking at product recommendations/analysis tools, such as those employed by sites like Amazon. These tools recommend products based on user preferences and previous buying behaviour, so that each person is fed customised product recommendations, without having to search around themselves - this improves satisfaction while reducing time spent searching through a crowded marketplace to find interesting products. The more relevant the recommendations, the more likely the customer is to keep purchasing (and the more revenue you'll generate).
AI can also be used to improve demand forecasting and order fulfilment, for example, by modelling trends, both long and short-term, in terms of sales data. This will help you predict future sales volumes more accurately, allowing you to plan ahead and make sure that you have enough stock on hand to meet customer demand. A better understanding of trends will also allow you to respond more quickly to market changes - for example, if certain products start selling faster than expected (or slower), then this can be considered when planning future orders with suppliers.
Finally, AI is having a growing impact on customer service, especially through the deployment of bots. Customer service bots are designed to help manage the flow of customer interactions, allowing businesses to provide a better service while using fewer human resources. For instance, a chatbot can be used as a customer support agent, answering simple questions and directing users to more detailed information as needed. Using AI-powered automation software like Zendesk (which integrates with other marketing and sales systems such as Salesforce), companies can automate some or all of their customer support workflows, while ensuring they still provide high-quality interactions with customers who need help.
The future impact of AI on life science marketing
There are so many things that life science marketers must do every day: conduct market research, shape messaging and strategy, plan campaigns, drive brand awareness, generate leads, qualify leads, engage with customers and prospects, measure the success of programs etc etc etc. That's why the future of scalable life science marketing is likely to be driven by AI in some way.
AI will enable marketers to create more personalised experiences for customers based on their individual needs and wants, leading to increased engagement, customer loyalty and sales (all while saving marketers time and effort, freeing them up to focus on more strategic or creative tasks). Marketers can also leverage AI to help them understand their customers better, while surfacing insights from large data sets that humans might miss.
The use of AI in marketing is fast approaching the point where we are moving beyond seeing it as simply a curiosity, and rapidly it will become a necessity. To help life science marketers have the biggest impact, we believe that we will all need to keep on top of developments in this area, including more proactively exploring how we can use the emerging technologies available to our advantage.
We’ll be providing future updates on AI in marketing, as well as staying on top of a number of other emerging trends. If you’d like us to help you stay in the loop on these types of technologies as they impact life science marketers in the future, sign up to our monthly email newsletter.