Whether it’s food, music, movies, clothes—anything really—as consumers we have our own preferences, and expect these interests to be catered to.
The world has outgrown the phase where greeting someone by their first name in an email is ‘personalisation’. Customers expect much more. They are time-poor, and they are looking for easy ways to connect with brands. This means seamless experiences that feel like a part of their everyday life, instead of heavy promotions & aggressive marketing.
To a business, some customers are high value and some are low value. But from a customer point of view, they are all equal, meaning they all expect an experience that nudges them in the right direction.
Across all the startups & corporates we've worked with, the proven recipe for sustainable growth is a combination of clean data infrastructure, hyper-personalised customer experiences and rapid marketing & sales experimentation.
And consumer data clearly spells out the sentiment; they expect customisation throughout their entire journey.
72% only engage with messages customized to their interests
80% only frequently shop with brands who personalise the experience
63% stop purchasing from companies who provide poor personalisation.
This last stat can be a huge problem, as companies often have the right data and the right tools to get personalisation right, but because of wrong measures or processes, they are creating more detractors than advocates.
Looking at all three stats more broadly, it can be particularly alarming given personalisation is rearing its head into every stage of the funnel, in particular from acquisition through to retention.
This demand is a result of natural progression. In the 80s and 90s, it was (mostly) about disrupting the right industry, building the right product, and growing into a trusted brand. In the last 20 years, it was still about building the right product, but trust was harder to gain, so stellar customer service became paramount to differentiate companies.
Now, it’s a step beyond that—and it’s about being data centric. These days, similar companies are differentiated on data, because those with access to all their consumer data are providing tailored experiences for every customer.
To deal with the demands of this new era and offer truly tailored experiences, you need a modern tech / data stack that can accommodate it.
Practically, you need the ability to send entirely unique communications (from marketing to onboarding) to every customer, no matter the channel they are interacting with. You especially want to be able to do this for your most loyal customers. Get this right, and you have the ability to create really unique and engaging customer experiences.
As an example, Woolies no longer sends standard weekly ‘specials’ to its Woolies Rewards customers. Instead, they send completely personalised specials based on a number of queues—including their purchase history and which Woolies they are commonly in proximity to. This is extremely effective for a number of reasons.
Firstly, it gets people into the store, with natural cross-shopping benefits. I will be drawn into Woolies for ½ price on any Kettle chips (obviously), and it’s very likely I’ll be picking up a couple other things while I’m there. Secondly, it’s also great from a yield management POV because these discounts are applicable for individual people. So not only are Woolies able to drive growth, they can also direct it by only giving discounts to people that need the incentive to get into the store. For someone whose data suggests they would buy those chips regardless—sorry pal, you can pay full price.
Personalisation opens up a number of exciting opportunities for how you engage with customers across the funnel.
Personalisation gives you unique ways to acquire customers.
Here is a personal favourite example of ours. Deutsche Bahn and Ogilvy used an algorithm that identified thousands of German locations that looked like international hot-spots, then targeted locals who had shown interest in visiting them. They compared New York to Frankfurt, Oregon to Bavaria and showed just how beautiful similar experiences were locally, just a train away, for a fraction of the price.
This personalised approach saw a 24% boost in revenue and the best ROI of a campaign in their history.
Practically speaking, at the acquisition stage, retargeting can generally be made more effective by switching from generic brand-based retargeting (i.e. just pointing back to your website) to product-based retargeting (what they were looking at)—or in the case of software, need-based retargeting (customer segments based on a common set of needs and purchase behaviours). Dynamic retargeting is a must for any modern businesses, and this personalisation can also support other, direct communication campaigns (e.g. your up-sell and cross-sell efforts).
Personalisation also provides unique ways for you to activate your customers from a sign-up to a paid user.
For our client Order In, Australia’s largest corporate catering platform, we built an infrastructure that enabled personalisation at scale. We sent tailored and automated onboarding and recommendation communications for new customers through both email and in-app messages. This was personalised based on both user/account traits and explicit preferences (for example, recommendations based on what offices located near them were loving). It was also based on their early user activity (we sent educational comms showing them how to use features they had not explored).
This personalisation led to a 58% faster time to first order.
At the activation, retention, and monetisation (revenue) stages, personalisation can tailor the onboarding experience for users based on self-selected needs or implicit requirements—whether in-app or through other direct communication channels like email, abandoned cart, ‘what’s new’ or ‘since your last order’ communications. In each stage of their journey, the customer will receive as close to the individualised key account manager (KAM) experience as possible, without an actual KAM there to follow up and guide them along the way. They’ll be shown exactly what they’re after once they’re in, and in many cases will build a trust that will shine through in your retention and monetisation metrics.
Outside of onboarding flows and drip campaigns, relevancy can also be provided independent of user traits—for example, if you’re operating a food business you may want to push promotions before lunch-time (and if they are direct-response make them time-sensitive). Data like date, time etc. offer an additional layer of personalisation, and when combined with unique promotions can offer a lot of value to your customers, bolstering your activation/retention metrics.
For our client Cabcharge, we were tasked with validating the business case for personalisation. Our goal was to re-engage their orphan and offline-only accounts with their new online product. We decided that our objective was to try and get these customers to an ‘aha’ moment with as little effort as possible, and by that I mean a moment where the customer goes ‘aha—I actually need this’
The most famous ‘aha’ moment in the growth world is Facebook’s ‘7 friends hack’ where a deep-dive into user behaviour found that the moment a user was hooked on Facebook, was the moment they had 7+ friends. Once they uncovered that, the onboarding flow for new Facebook users was heavily focused on finding, recommending and engaging with friends as quick as possible—and their global dominance followed suit.
To achieve the ‘aha’ moment for Cabcharge, we automatically created accounts for these customers in the new online product, and then took personalised elements from the app data and sent that to them in an email—essentially saying ‘you haven't claimed your free account, here’s the information you can have access to.’ This campaign outperformed all benchmark campaigns significantly; with click-through-rate up 18%. Across the different variants of personalisation, retention improved across all metrics.
Circling back to your first interaction with customers, you might be surprised at the level of pre-sign up personalisation you can provide. Tools like Clearbit are fantastic for showing content for users based on industry. For example, a user working for a bank is likely more interested in testimonials, case studies and other marketing assets, copy and imagery from other financial services. This level of personalisation can also be achieved at a more granular level (and significantly cheaper) through dedicated landing pages based on needs, industry or other relevant criteria.
Generally, landing-page based personalisation works better for paid channels. This can be achieved through a CMS set-up using a tool like Webflow. You can check out our guide to building fast, beautiful websites without development help to learn more.
Companies that have cracked the code for personalisation are doubling down on their analytics stack and automation efforts.
You are seeing significant improvements, not only for start-ups and scale-ups, but established corporates: 50% reduced acquisition costs, revenue lifts of 5-15%, and conversion rates, lead gen, visitor engagement, customer experience and brand loyalty all improving. You’re seeing a shift to more organic, sustainable growth. These are the kinds of alluring stats that are drawing companies into a more data-centric approach.
Interestingly, this allure isn’t new as data-driven and personalisation aren’t particularly new concepts; they’ve been buzzwords for a while now. Despite this, the opportunity is largely untapped. Although 89% of companies are investing, only 36% have even basic website personalisation.
In our experience, there are a few things that are holding companies back from achieving best-practice data handling and personalisation.
Things can be difficult when a company has a more traditional approach and culture data & growth. This is a natural product of bigger companies, as structure and process is often necessary for order. But it can also appear in scale-ups too, who can become over-invested in some of the legacy processes they set up in their formative days. Regardless of companies, this issue usually manifests in a couple of ways.
Firstly, a siloed approach to teams. By this we mean that sales is purely sales, marketing is purely marketing, and there is little collaboration across disciplines. In this set-up, companies will often compete with themselves internally, setting up internal KPIs where departments compete against each other (for who achieves best sales, margins, best outcome). What they really forget is if they shift that competition externally, they can combine all that energy to focus on increasing market share.
Because growth is not only about customer acquisition, it involves retention, activation, pricing strategy and product development. That means growth is everyone’s job. And everyone can and should be able to be able to see data, draw an insight and contribute an idea. It’s still possible to have robust company structures, processes and meetings in place with a highly agile culture.
The second issue is that many business struggle to strike a balance between providing highly personalised customer experiences and ensuring the scalability of their product/service. Practically, this is because businesses typically have a few, core high value customers, and then many smaller, low-value ones. Retention metrics for high value clients will often look significantly better than for smaller clients—a no-brainer given the focus and highly individualised service they receive.
Businesses in this position often make two key mistakes:
1—Lowering the qualification criteria for ‘key accounts,’ i.e. giving staff a bunch of the lower-value clients and expecting them to deliver the same individualised experience as high-value clients in an effort to boost performance.
2—Neglecting smaller accounts all together as they are ‘not worth the effort.’
The problem is that (1) can easily bog down your account management and customer service team in requests from small accounts, impacting service quality for a low potential gain in revenue, and (2) easily becomes a self-fulfilling prophecy. In either case, the smaller accounts will usually receive less personalised communication.
This problem goes hand in hand with the final problem: a ‘fear of failure’ culture. Many times, companies will view avoiding poor results as more important than success. This limits their creativity, leads them to take risk-averse choices, and even leads them to shift goalposts mid-campaign to demonstrate success. Sometimes a misguided approach to being ‘data-driven’ can lead teams to be blinded by pure KPIs & short-term results, instead of looking at how to set up effective, long-term automation strategies to push relevant content to all accounts, at scale.
Practically, this leads companies to circle back to traditional ‘spikey’ communications when instead they should be focusing on layered strategies.
These spikey strategies are things like newsletters, discount promotions, and doubling down on paid channels, which are necessary to ensure they meet KPIs and see a spike in revenue. Where as layered marketing is more subtle, personalised and engaging marketing throughout a customer’s journey.
Spikey strategies do not create lasting performance improvements—the effect dissipates quickly, requiring an even stronger incentive to reach the next target. 10% becomes, 15% becomes 25%—until eventually your customer drops off. That said, we don’t necessarily discourage newsletters, we just discourage heavy reliance on them as they are high effort tasks that can bog down your teams without adding much long-term value to the customer or the business itself.
But they can, in fact, also benefit from personalisation—whether that’s more granular newsletters separated based on industry, subscription type etc., or newsletters which feed in interesting customer data points. This is commonly done in the e-commerce space, but can also be applied to SaaS.
Broadly speaking, layered strategies are much better as they are more engaging, build trust and increase lifetime value. Improving these campaigns is an investment that impacts all future (and in some cases current) users, as opposed to one-off communication which needs to be recreated with fresh content each time.
To give you an example of spikey vs layered marketing, recently, like many of us—I’ve been updating my home office, the main purchase being new monitors. I visited Kogan and Umart, browsed only at monitors, and looked specifically at around 5-6 monitors. I then signed up to both websites, deciding to wait and see what deals they’d offer me as a member.
Kogan continued to send me a lot of irrelevant and unnecessary promotion emails (I’m not interested in 10% of all furniture). Umart, however, sent me curated deals, with unique monitor discounts and combo packages. These were the same monitors, & same delivery time that drew me to both websites—but I had a completely different experience with each. Companies are differentiated on data and their ability to personalise—and you can guess where I decided to shop.
The second thing that can hold companies back is that they often aren’t using the right tools. This is because the analytics status quo isn’t best practice anymore.
There is a stock-standard ‘out-of-the-box’ combination that most companies, regardless of industry, will follow. This includes Google Analytics, Google Tag Manager, Heat Maps and some combination of backend and CRM data.
This is a great starting point and it is powerful. You can get it up quick & easy, start feeding it into some reporting tools, gather some insights & run some experiments based on them. But in the hyper-personalisation era, this is the bare minimum.
You need to make data simpler, and you need it in one place—in your own database (instead of it sitting in tools). You need to be able to attribute every campaign you ever run precisely; this stack above is notorious for its limitations in attribution modelling. You need to have your data clearly visible and accessible on-demand, for everyone. Whether that’s automated reports pushed to individual teams for day-to-day management, or more specific reports that they can pull on a needs basis—no matter who it is, they can pull the same report and it delivers the same KPIs as a sole set of truth. No more consolidating across different sources of data.
Finally, of course—the ultimate reward for the right set-up and clean data; you need to be able to create behavioural & personalised campaigns, easily, and actually experiment with it effectively. To do all of this effectively, you need a customer data platform. In our experience, the best CDP is Segment. A CDP is an engine room for your customer insights, and your marketing automation. It gives you clear, actionable insights into true customer behaviour (for example, how often they are ordering, how valuable they are, and if you are creating loyal customers). If you gives you a single customer view based on events in their lifecycle.
The final reason why companies are struggling is simply because the advances in the space are new, and are hard to implement correctly.
Getting personalisation right requires business acumen and funnel understanding, and cross disciplinary expertise in growth, monetisation, marketing, analytics, product development & engineering.
There’s no out-of-the-box solution, especially if you are migrating an existing set-up. There are a lot of things that can go wrong (e.g. data interruption) so it becomes a bit like changing the wheel on a moving car, or a bit like this impressive jump below.
Many companies do not have a single person with this skill-set. Therefore, the typical solutions are to either coordinate a huge cross-company project, or to pull in external consultants like ikaros who can bridge the gaps between teams to make this happen.
So that’s an overview into personalisation. The specific tools, personalisation strategies and channels you use will depend on your business’ current set-up and goals. If you get the infrastructure right you are guaranteed to start seeing much nicer conversion metrics and most importantly—put yourself on the journey to sustainable growth.
Just remember, it is always important to put yourself in the shoes of your customer and make sure that the personalised experience you’re providing adds relevancy and value, and isn’t just personalisation for the sake of personalisation.