SwiftERM Hyper-personalisation for ecommerce email marketing
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Personalisation is essential to email marketing

Hyper-personalisation is essential to email marketing

Consumers have come to demand and expect relevant and hyper-personalised content and experience, both online and offline. To meet those demands, marketers are striving to leverage email hyper-personalisation to move toward one-to-one experiences that not only meet but exceed consumer expectations and set them apart from the competition.

What is email hyper-personalisation?

Hyper-personalisation, in the context of email marketing, is the act of targeting an email campaign to a specific subscriber by leveraging first-party data and information you have about them as an individual, not part of a collective or segment. Ten years ago you’d be offered articles telling you it is information like their first name or the last product they bought, where they live, how many times they log in, or several other data points. Today, it is every nuance of that individual’s life when they visit your site. The length of time they browse items, what they return to, when, where they exit to, and importantly the thought process which culminates in a buying decision etc. But beware wherever you read the word “segmentation“, remember it is not hyper-personalisation. (As the research will illustrate below this equates to 20x less ROI).

Hyper-personalising your email campaigns is a proven way to increase your open and click-through rates and can have a measurable impact on your ROI and revenue. Studies have shown emails with hyper-personalisation are 26% more likely to be opened than those without.

These results stem from the fact that hyper-personalised emails are more relevant to subscribers. Instead of receiving a campaign with generic offers and messaging, your subscribers will receive an email that is targeted directly at them, includes their name, and provides offers (products, promotions, etc.) that are relevant to their interests.

It is important to be discerning here, as many articles still flourish online. The distinction between the leading hyper-personalisation vendors is significant In fact, so important are the smallest changes made by each impression, that rarely do they ever get the same content twice. If any pattern (and therefore explicitly alternate pattern too) is established, the artificial intelligence of a machine learning algorithm identifies it, notes it, and ranks it.

But instead of acting immediately on it, what it does is rank that pattern in comparison with others, selecting only the one that delivers the highest buying propensity in choices of product to offer. So if Kylie clicks on a “sparkly top” 7 times, and stays on it for a minimum of 3 minutes at least twice, she might have a likelihood of buying it 27% higher than another sparkly top, visited in the last 5 visits. But if an abandoned cart item (for her) outperforms the above equation, chances are offering that product first would prove more beneficial – the permutations are endless. Now compare this to segmentation, where poor Kylie is merely lumped together with everyone who had bought a top in the last 3 months. Yipes! You can see why sales disappear into oblivion in comparison. She just wouldn’t be able to get you out of her head!

Keeping with the same analogy, if having sent the item it is neither clicked on, or indeed the email not even opened, without the facility (time, money, effort etc) to understand what happened, the algorithm can use historical data from the same process, to decide how much to adjust the Sparkly top in relations to its product peers up or down, according to only Kylie’s actions. In this case, it would be reasonable to suggest unopened keeps it up the pecking order, while opened and not influenced to browse let alone buy, would see it moving down the propriety list pretty rapidly. Acknowledging that there are many more reasons why she might not have opened it that a professional algorithm takes into consideration, not least of which is being on holiday.

Performance propels outperformance

Research from McKinsey shows that hyper-personalisation most often drives up to 20x the revenue lift (with company-specific lift driven by sector and ability to execute). The more skilful a company becomes in applying data to grow customer knowledge and intimacy, the greater the returns. For digital companies that forge a data-backed, direct-to-consumer model, hyper-personalisation isn’t just how they market, it’s how they operate.

Those leading the charge in hyper-personalisation also have better customer outcomes. Their focus on the relationship and long-term value leads to better upward migration, retention, and loyalty.

Hyper-personalisation can also be a revenue accelerator even for businesses that typically lack direct access to customers such as companies in the consumer packaged goods segment. Among these companies, those with the fastest rates of revenue growth were far more likely to prioritise hyper-personalisation than slower growers. The research suggests that even small shifts in improving customer intimacy create competitive advantage – and these benefits grow with maturity.

Out-performers organise their business around hyper-personalisation

Companies that achieve the best results from hyper-personalisation approach it differently. Rather than seeing personalisation solely as a marketing or analytics problem, they view it as an organisation-wide opportunity. Rather than focusing solely on short-term wins, they look for long-term drivers of growth and emphasise customer lifetime value.

Hyper-personalisation to succeed in challenging times

If you were interested in a company’s product or service, and that company found a way to reach out to you with a message that showed they wanted your business and truly understood your needs, would you be more likely to buy? Of course, the answer is yes. But the real question is – can your company survive when competitors are doing the same to your customers?

The good news is that it’s easy to stay in the game. Simply invest in an automated, hyper-personalised marketing strategy use a machine learning autonomous hyper-personalisation email marketing campaign as a kick-off point, and watch the leads flow in. You won’t regret it when the time and energy spent is paid back quickly in increased sales you’ll wonder how you ever did business without it.

Hyper-personalisation and personality

One thing about DTC buyers is they love to feel a connection with the brand they are buying from; a way to show off their personality. Stick to the integrity and story of your brand but embrace the new ways of storytelling and marketing that highlight how your products are different from its competitors. By writing engaging product descriptions, showcasing materials and designs on the website, and more, there is a myriad of ways to emphasise a product’s uniqueness. Embrace other unique ways to sell products with merchandising or special releases.

It is essential to adopt technology to embrace online highest returning experiences enjoyed by customers elsewhere in their lives. Email marketing for example can now surpass hyper-personalisation to each individual by including send-time optimisation as well, which in comparison to its peers leaves it standing as far as ROI is concerned. The introduction of hyper-personalisation for email marketing has surpassed all the comers by a country mile. Hyper-personalisation email solution SwiftERM use every facet of data collected including much not stored even by the most advanced platforms themselves, but rather by a specialist SaaS plugin that retrieves the information for you. It then analyses it to identify what each unique consumer is most likely to buy next and when. When doing your calculations take into account that it is 100% autonomous, so no staff overheads whatsoever.

Imagine knowing exactly what product each person will buy next, and having a means to be able to present that exact item to them, before anyone else gets a look in. Abhorring segmentation, as the practice of shutting the wrong people in a room together always works, not.

Only you have the benefit of the knowledge of everything going off on your website. There is a pattern created by each consumer’s activity, each visit for example typically leaves 100 impressions per visit, Each suggests a strategy both rare and personal to that one person. Not forgetting what they don’t look at or fail to be attracted to at that instant is equally important to clear the way for things that are. Market research companies including McKinsey and Statista both offer a figure over 20x the return of traditional email marketing.

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