The world – especially the “digital” one – is evolving at breakneck speed. Just think about AI. The generative tools that now seem to be embedded in a majority of peoples’ workflows are all less than a year old. Granted, teams of developers have been relentlessly building and fine-tuning them for years, but our use of them for everyday tasks is very recent.
This increased velocity is impacting every corner of the modern business. Marketing is no exception – and you might wonder how AI is being leveraged in modern startups to improve their growth metrics. In this article, I’ll be using the AARRR framework, a popular and important way to look at growth in a startup context and one that I’ve used to structure my growth efforts for the better part of the last decade, to break down its impact.
The AARRR Framework
The AARRR framework, also known as 'Pirate Metrics' was coined by Dave McClure, the founder of 500 Startups, an internet startup program and seed fund, around 2007. It stands for:
- Acquisition: Getting users to your product from various channels.
- Activation: Ensuring users have a happy and quick first experience with your product.
- Retention: Making sure users return and use your product repeatedly.
- Referral: Encouraging users to refer others to your product.
- Revenue: Monetizing the user behavior.
The AARRR framework provides a complete view of the customer journey, and it has helped me tons over the years in identifying opportunities and bottlenecks in my growth processes.
Better customer acquisition with predictive analytics, AI campaign improvements & sales intelligence
In the age of AI, several tactics have successfully been implemented to improve acquisition – i.e., getting more people to your product without spending more. One of the most common ways that AI is being used today to boost customer acquisition is the implementation of predictive analytics for better lead scoring. Indeed, AI can be used to analyze a vast amount of data from various sources such as website visits, social media interactions, and purchase histories. This analysis can help identify patterns and predict which leads are more likely to convert into customers, improving the efficiency of sales efforts. Salesforce, for example, uses its AI tool, Einstein, to offer predictive lead scoring for businesses.
At designstripe, we’ve been taking advantage of AI to simplify and summarize advertising reports. Thanks to plugins, ChatGPT is able to read csv files, interpret the data and give us insights into which campaigns are working and which aren’t. What’s more, we’re also able to ask it for recommendations on campaign improvements. This is something that we’ve only begun testing, but that we believe will help us get a better ROAS and improve our customer acquisition efforts.
Another way that we’ve seen AI being used for customer acquisition is with the use of chatbots for immediate customer interaction. AI-powered chatbots can interact with potential customers on websites or social media platforms, answer their questions, guide them through the sales funnel, and even help them make purchases. A good example of this is Drift, who has developed a conversational AI bot that can be custom-trained on companies’ sales material, helping them close more pipeline without spending more on sales reps.
Removing hurdles to activation
Once you’ve managed to get some traffic to your website and you’ve acquired new users, you have to start thinking about activating them. This involves ensuring that your new customers are taking the desired actions on your platform and ensuring that they have a happy first experience with your product. In my view, what we call activation, in the context of the AARRR framework, is often found in the product onboarding phase.
It’s no secret that we all want our potential customers to activate as quickly as possible. At the same time, we want to be able to gather as much information as we can about these people in order to retain them and re-engage them later down the line (we’ll get to that later). It’s a tough balance to find. That’s why we’ve been looking into automatic contact enrichment with AI – by using tools like Zapier, ChatGPT and Apollo, we’ve been able to get complete customer profiles with a person’s email address only. CRM companies like Hubspot are also developing their proprietary AI products for contact enrichment.
These tools and practices have the benefit of allowing users to get through onboarding and to the actual product by entering minimal information, while AI tools in the background work to enrich this new contact in the CRM with additional information like company name, location and company size. This then makes it easy to have a complete overview of each of our customers, and start to build personalized experiences to keep them engaged.
At designstripe, we leverage AI to speed up activation on our newest product, Smart Layouts. By simply typing in their brand’s URL, users get a complete brand kit in seconds that will be used to create on-brand social media posts. They can also fine-tune certain aspects of their brand profile like their company description with our integrated AI. This makes the whole onboarding process faster, easier and more accurate – helping users get to the product as fast as possible.
Personalization at scale for better retention
Retention is all about keeping your customers engaged and coming back to your product. For most, retention is the mother of all growth – it’s the hardest to get right, but once you do, your road to exponential growth is paved. One of the reasons that it’s such a hard metric to influence is because spending your way to good retention is very difficult. As opposed to acquisition, where companies can increase their ad spend, or referral, where they can increase their incentives, most of what impacts retention metrics are found within the product.
That said, marketing can still play an instrumental role in retaining users and keeping them engaged, and we’ve seen it first hand at designstripe. Here too, AI has made the lives of our marketing department easier in helping us craft the right messages and experiences to reel customers back in and boost our retention metrics.
For instance we’ve been experimenting with AI to design effective email marketing campaigns. It can determine the best time to send emails, predict the subject lines that will get the most opens, and even personalize the content for each recipient. Tools like Persado and Phrasee provide AI-based email marketing services that help with just that. Apollo has also rolled out its own AI to help craft hyper-personalized emails at scale.
AI can also analyze customer behavior and preferences to personalize marketing messages and product recommendations. By delivering more relevant content, companies can improve engagement and conversion rates. An example you will for sure recognize is how Netflix uses AI to offer tailored movie and show recommendations, significantly improving their user engagement and retention.
AI’s potential in helping companies get referrals right
Next comes the referral step. Referral involves turning your satisfied customers into advocates who actively refer your product to others. Referral programs are very common nowadays, especially for consumer products. B2B SaaS companies are also increasingly implementing referral programs and finding success. I’ve been particularly interested in the mechanics and success factors of B2B referral programs since the start of my career – I even took part in building the first version of Pleo’s referral program several years ago, when the concept in a business software context was fairly novel.
What I found is that succeeding at getting your users to refer your product to their friends primarily depends on three things: i) making a product people want to talk about, ii) identifying the right potential advocates and iii) finding the right incentives. From my experience and research on the market, we’re still very early in terms of specialized AI tooling for improving referrals. However, I’m excited to see the developments that will certainly be coming in the near future. One use case that I’m particularly interested in is AI’s ability to predict and help identify the right potential advocates – the ones that are most likely to refer designstripe to their friends. I’ve also begun summarizing the best B2B referral programs using ChatGPT and LennyBot, which has made my job a lot easier in terms of figuring out the best way to put a program in place and the right incentives to give.
Pricing: from guessing game to AI-based
Revenue, the lifeline of every business, is the result of successfully turning active users into paying customers. It’s the final and arguably the most important metric in the AARRR framework. Without it, your business doesn’t exist for very long.
Taking a high-level and simplified view, revenue can be influenced in one of three ways: i) getting more people to buy, ii) getting people to buy more and iii) increasing prices. AI can help with all three of these tactics.
AI-powered pricing is one way in which a growing number of companies have managed to impact their revenue. Indeed, according to a recent article by VentureBeat highlighting the phenomenon, “AI-pricing algorithms are trained to listen to customers and determine the most favorable prices for enabling purchases”. These models take into account hundreds of data points, such as competitors, promotions or how customers look at certain products, and make pricing recommendations. With Smart Layouts currently being in closed beta (you can join the waiting list!), we still have some work to do on the product’s pricing. But with the plethora of tools at our disposal and with the capabilities mentioned above, it seems like we have part of our work cut out for us. We’re looking forward to experimenting on that front and reporting back with our findings.
AI has made a lasting impact on Growth Marketing – but it’s only the beginning
Embedding AI tools and practices into your marketing strategy can lead to better outcomes at each stage of the customer journey – from better acquisition to higher revenue. That said, AI is only one piece of the puzzle, and shouldn’t be treated as a one-stop solution that can fix all of your company’s growth problems.
Companies need to have a product that people want, a great brand that people can build affinity with, a team that can help move the ship forward and unit economics that make sense. Once these elements are in place, I believe that marketing and growth teams can tremendously increase their effectiveness and improve their results by integrating AI tooling into their workflows.
We’ve seen it first-hand at designstripe – AI has brought us tremendous opportunities to reshape and innovate our marketing and growth strategies. However, it's only the beginning. The landscape of AI tools for growth is ever-evolving and will continue to bring forth new methods and technologies. So I invite you to stay connected with us as we navigate this exciting frontier, and leverage our insights to continue building upon our new tool, Smart Layouts. It's a promising journey into the future, and we're thrilled to have you on board as we explore the potential of AI in driving sustainable growth.
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