New tech out-personalises 'old school' approaches

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By: Wise Marketer Staff |

Posted on March 30, 2015

Personalisation is a major priority for marketers today but there isn't a single standardised definition, making adoption difficult to manage, according to Neil Capel, CEO for Sailthru, who here explains how to identify modern technologies and understand the true level of personalisation that mature solutions can deliver.

There are many variations of personalisation, and as technology is maturing, the potential for true one-to-one relationships with thousands of customers has become a reality. And with a vast array of technology vendors pitching personalisation, it is easy to assume marketers have widely adopted the approach. But inconsistency between what one marketer and another might consider personal is creating friction in the customer experience and holding brands back from realising the true potential of personalisation.

In the true sense of the word, personalisation is about individual users, their behaviours, interests, needs, wants, desires and engagement patterns. However, what's possible today is far more than the behavioural segmentation strategies that have characterised personalisation for years. Modern personalisation is an approach that considers a myriad of data points about behaviours, uses and situations and extends to every aspect of messaging.

Today's most advanced technologies enable marketers to get down to the segment of one, using algorithms that specifically tailor marketing to the individual, not just to the segment within which they're categorised. By using thousands of data points attributed to each individual customer, collected from all channels by one integrated platform, modern personalisation ensures that every single one of your customers experiences your brand uniquely, regardless of when, where and how they choose to engage, for example:

  • Behavioural - device tendencies, geo-location factors and times of day.
  • Usage - Recency-Frequency-Monetary value (RFM) includes search results, abandonment, win-backs, shared attributes of product views, and influences such as free shipping.
  • Situational - the 'why' of someone's browsing or buying behaviours.

The most important concept for marketers to understand is that personalisation is ever changing. This is driven not just by advancements in technology, but more so by ever-changing consumer behaviours. If you asked consumers three years ago whether or not they desired personalisation, they'd most likely respond with blank stares. But today, consumer awareness and thirst for personalised experiences is radically different. They are both aware and keen to see brands take the personal approach. And as their behaviours and desires continue to shift, personalisation must also evolve.

And, evolve it has. Not just in terms of the end-user experience, but also in terms of revenue generation. To make this more tangible for marketers, we can view personalisation on a 'maturity curve' or ladder that maps the specific approach to the potential gains:

  1. Batch and Blast
    An email marketing technique that promises 'the more people you email, the more chance of engagement among those you send to.' This isn't personalisation at all! It's just a baseline to show how the first step in personalisation does result in revenue gains.
  2. Field Insertion
    Simply adding in someone's name into an email used to be a sign of personalisation. A client recently told me that when they first used customers' names in emails, they saw a five percent increase in conversion rates. That's extremely promising, but it's just a drop in the ocean compared to results from modern technology.
  3. Segmentation/Rules based
    Segmentation is not new at all, but many personalisation technologies that started as Email Service Providers (ESPs) are founded on this exact approach. This form of personalisation is characterised by pre-defined rules, (i.e. 'If user is male, serve this treatment') and is limited to serving customers based on explicit signals, such as gender, geo and age. While it's an approach that delivers more revenue than field insertion, it is still not really personalisation at all.
  4. Behavioural Recommendations
    This point on the maturity curve is incredibly important. It's where the vast majority of technologies play and as you can see, it's still a far cry from delivering the highest revenue potential. Legacy ESPs and today's 'marketing clouds' tout this approach as being advanced. Some are even calling these recommendations "predictions." But don't be fooled! Behavioural recommendations are simply an extension of segmentation, whereby the data points leveraged go beyond basic demographics to include response and conversion data, channel-specific engagement data and transactional data.

    Offering product recommendations to your customers based on their recent purchases is far more personal than the previous approach, but by not incorporating all the behavioural and interest data that can be accessed from all channels, this approach fails to meet the expectations of today's consumer. The hallmark of the approach is the phrase 'others who purchased X also purchased Y!' The approach is most often used to serve a user with products based on what other similar users have followed and bought. This does not get down to individual level, so it's still not really personalisation.

  5. Omnichannel Optimised
    Personalisation that comes from combining data from multiple sources and responding in real-time in ways that go far beyond just recommendations. This is about creating a connected experience for each individual user where message, content, channel, time of day, discounts and calls to action are all fully dynamic. Think 'big data' and big revenue. The technologies that can support a marketing team in delivering this experience are few and far between. They're natively built for big data scale and for collecting data from all channels, rather than through acquisitions and integrations. They consider the full depth and breadth of customer data and use algorithms to automate personalisation for all individuals. They house data in a flexible database and create a unique data asset on each individual user. They enable a true, personalised experience across multiple channels.
  6. Predictive Personalisation
    The most modern form of personalisation where the impact on revenue is the most impressive. This personalisation is based on predictive tools that use models to answer questions that get to the heart of what marketers care about. Questions such as: When will they buy next? How much will they spend? Will they open and read email? By combining these predictions with personalisation at the user level, marketers are able to not just recommend content that is relevant, but also tailored based on those predicted behaviours.

    The challenge with this form of personalisation is that marketers must identify a technology that combines omnichannel data collection, automated cross-channel personalisation and predictive intelligence in a single platform.

"It's critical for brands to understand the maturity of any personalisation solution because the face-to-face, loyalty-producing interactions facilitated by in-store shopping experiences are becoming an endangered species. Smart brands are laying the foundations now for connected, contiguous engagement across their digital ecosystems," concluded Capel. "That engagement will be driven by personalisation that allows marketers to show customers and prospects content that is of genuine interest to them. Customers appreciate this. They enjoy it. And increasingly, they're demanding it. It can be the deciding factor between choosing one brand over the competition."#

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