Personalisation is everywhere. It’s in our Facebook feeds, on our Netflix queues, and increasingly, in our shopping experiences. Ever since retail giants such as Amazon proved the value of personalisation online, smaller retailers have been searching for ways to adopt the practice into their own businesses on a smaller scale. Unfortunately, while most retailers have good intentions when it comes to personalisation, few have been able to incorporate the trend in a way that maximises its full potential.
The big question is, does marketing to individuals defeat the benefit of the internet as a mass communications tool? By relying on a more targeted – and increasingly automated - approach, are marketers simply cutting down on the number of potential prospects that they could reach? This is the paradox of mass personalisation, sacrificing broad reach for a handful of hyper-targeted leads.
So how can marketers ensure that they’re not missing out on vital prospects through over-individualised marketing? Here are three ways to avoid the paradox of mass personalisation and ensure that your targeted marketing is hitting the spot:
1. Rely on quality data
If businesses are going to tailor their marketing to highly specific audiences, they must ensure that they are hitting their mark every single time. As it stands however, as many as one in four marketers are unable to provide targeted marketing initiatives as a result of poor quality data.
If a business is relying on inaccurate or incomplete data, their mass-personalisation efforts will be doomed to fail from the very start. While the wide variety of tools available to marketers makes it increasingly easy for anyone to create and distribute a personalised email or SMS campaign, without the right data in place to begin with, the benefits of personalisation simply won’t translate into real-world sales. Until marketers know exactly who their personalised message is targeting, all they are doing is cutting down on the number of prospects that will see their message.
2. Segment effectively
One of the biggest factors holding personalisation initiatives back is an inability to effectively segment customer data. According to our research, 91% of marketers aren’t currently segmenting customer data in real-time – a vital step required for accurate and effective personalisation of content and recommendations. While this is currently holding marketers back, 51% of marketers believe that they are at least moving towards the ability to segment in real-time. Given this changing trend, we should expect to see a drastic increase in the effectiveness of highly-targeted personalised content online using up-to-date online behaviours.
3. Think outside the box
Too many marketers allow simplistic correlations and broad trends to drive their personalisation approach online. More often than not, customer purchasing decisions are far more complicated than simply “the customer bought X previously, therefore they’ll buy X again.” Rather than relying on these basic correlations, marketers need to pull together multiple data sets around their customers, taking the time to analyse their relationships and identify the less obvious purchasing trends.
At the same time, marketers must also avoid the urge to over-rely on stereotypes. As an example, many marketers would assume that young people are the most likely to download and use a mobile banking app. In reality however, research from Bain Insights shows that older generations are by far the most likely to bank via a mobile application. By failing to examine the data and confusing targeting with stereotyping, marketers may miss the opportunity to adapt content to their most significant demographics.
4. The need for real-time, predictive analytics
With the amount of time being spent online and via mobile apps, the velocity of data collection is getting faster and therefore the need to analyse and segment customer data (known or anonymous) is a challenge. Marketers need tools in place that can do the analysis and segmentation autonomously, and in realtime. Machine learning and predictive algorithms need to replace the traditional analytics to ensure that personalization can be achieved in realtime to ensure maximum engagement with the customer at every opportunity.
Is mass-personalisation a point for concern?
While there does remain some contradiction between the role of the internet as a mass communications tool and the rise of personalisation online, it is not necessarily a contradiction that needs to be “solved”. For years, the way consumers browse online has been changing. More than ever before, internet users are seeking out highly specialised content which is designed to meet their very specific needs – this is a fact that brands must be willing to adapt to, and personalisation represents a great place to start.
For the moment, achieving personalisation on a mass-scale may not be possible. But, as technology evolves, the ability to manage individuals en-masse, and in real-time, without compromising on unique details will become far more widespread. Through the development of increasingly advanced customer data platforms many brands are already turning to technology to achieve this feat. Through the adoption of predictive analytics, artificial intelligence and machine learning, many of the world’s leading retailers are already overcoming the issues of personalisation in volume. By incorporating these tools in the right places, brands can achieve an effective degree of personalisation as and when it counts, while still casting a wide net within which to target potential customers.
This will be the future of personalisation online – reaching out to a wide number of people, and then using automation to apply relevancy exactly when it counts.
By Anthony Botibol, marketing director at BlueVenn
PrivSec Conferences will bring together leading speakers and experts from privacy and security to deliver compelling content via solo presentations, panel discussions, debates, roundtables and workshops.
For more information on upcoming events, visit the website.
comments powered by Disqus