Did you that according to RJ Metricsknow the top 1% of your shoppers are worth 18 times more than the average shopper<\/b>? <\/p>\n
This amazing stat begs two questions for retail marketers:
\n1: How can retail marketers engage the top 1% more effectively?
\n2: And how can marketers engage all consumers to convert them to top shoppers?<\/p>\n
Happily, there are immediate steps brands can take to improve revenues and customer lifetime value. In the past few years, a trifecta of powerful computing, big data, and machine learning have triggered a big shakeup in personalisation.<\/p>\n
Why has AI-based personalisation suddenly become so important? Because it works:<\/p>\n
- \n
- At Netflix, more than 80 per cent of the TV shows people watch are discovered through the platform\u2019s recommendation system<\/li>\n
- At Google, news recommendations improved click-through rate (CTR) by 38%<\/li>\n
- For Amazon, 35% of sales come from recommendations<\/li>\n<\/ul>\n
Personalisation is now a critical issue. And yet, email marketing often still operates with legacy technologies and segment-driven campaigns. According to E-consultancy, just 17% of brands and 21% of agencies are innovating with artificial intelligence to create personalisation at scale. So there are currently opportunities for marketers to differentiate themselves through an AI strategy.<\/p>\n
![\"\"](\"https:\/\/www.emailvendorselection.com\/wp-content\/uploads\/AI-emailmarketing-innovation-stats.png\")
<\/p>\nFor retailers and e-commerce brands, personalisation technologies are all about understanding the customer so the product sells itself<\/b>. Think about our examples from the retail and entertainment industries. From Spotify suggesting a playlist to Amazon recommending products to buy, they first understand each consumer\u2019s tastes then curate content for that consumer.<\/p>\n
![\"\"](\"https:\/\/www.emailvendorselection.com\/wp-content\/uploads\/AI-emailmarketing-taste-profile.png\")
\nA Spotify-style consumer taste profile, as applied in email personalisation<\/i><\/p>\nToday, shoppers demand relevance and personalisation in order to remain engaged. Statista found that the more personalised the email, the higher the email open and click-through rates. However, when we talk about hyper-personalisation, we\u2019re going beyond the \u201cDear Emily,\u201d intro and even beyond personalisation per audience segment. Nowadays, data-savvy marketers are using AI to adapt content for each unique consumer. <\/p>\n
Nobody phrases it this way, but machine learning in retail is primarily a marketing issue. It’s really an attempt to understand the consumer so we can serve them better.<\/p>\n
<\/span>The 3P key techniques of AI in email personalisation<\/span><\/h2>\n
AI techniques can be used to achieve multiple goals. So the best AI email personalisation technique will largely depend on your email marketing strategy. <\/p>\n
Email marketers can use the 3P\u2019s of key AI techniques,<\/strong> namely:<\/p>\n
- \n
- Profile-based personalisation<\/li>\n
- Product-based personalisation<\/li>\n
- Predictive Analytics<\/li>\n<\/ol>\n
<\/span>1. AI for Profile-based email personalisation<\/span><\/h2>\n
Great for newsletters and other campaigns to large audiences<\/i><\/p>\n
There\u2019s a trend toward more in-depth recommendation systems online. Spotify and Netflix have refined their recommendation engines to create more meaningful engagement with their customers through hyper-personalisation. <\/p>\n
For example, Spotify provides each individual listener with a tailored and personalised selection of songs, and while automated recommendations aren\u2019t new, Spotify’s complex algorithm isn\u2019t just based on a user\u2019s saved songs; it builds a taste profile of each user \u2019s musical tastes. <\/p>\n
![\"\"](\"https:\/\/www.emailvendorselection.com\/wp-content\/uploads\/spotify-discover-weekly.jpg\")
<\/p>\nThese entertainment brands have raised consumer expectations. Now retailers must also provide each shopper with curated content – not just based on a user\u2019s last click or purchase, but delve much deeper into their shopping tastes.<\/p>\n
Profile-based personalisation is particularly suited to email newsletter personalisation for the following reasons:<\/p>\n
1. Results tend to be highly relevant.<\/b> Because profile-based AI relies on each consumers ‘taste profile’, they are likely to be highly relevant to a consumer\u2019s interests. This makes profile-based AI especially valuable for organisations with lots of products and lots of consumers (think retailers, e-commerce and travel brands).<\/p>\n
2. Encourage product discovery.<\/b> Another advantage of this technique is that email marketers can use the shoppers taste profile to encourage browsing and shopping – even when the shopper doesn’t have a discernible need. By continually showing fresh and relevant content, email marketers can maximise product discovery and revenues.<\/p>\n
3. Marketers can get started quickly.<\/b> Profile-based personalisation avoids the cold-start problem that often bedevils product-to-product recommendation technologies. <\/p>\n
While the technology still requires some initial data to begin making recommendations, the quality of those early recommendations is likely to be higher than with a platform that only becomes statistically valid after millions of data points have been added and correlated.<\/p>\n
![\"\"](\"https:\/\/www.emailvendorselection.com\/wp-content\/uploads\/AI-in-email-profile-based.png\")
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