Email may not be seen as the most glamorous or interesting marketing channel, but it’s got a high ROI and can be the best way to reach your customer directly. New AI technologies are making email more engaging and exciting and it’s a sure way for any retail business to make money. For every £1 on email, £32 is made (DMA, 2017) and email is resulting in £29billion of online sales in the retail sector in the UK (Econsultancy). Algorithms can be extremely useful in getting to know your customer and making your email marketing work harder.
People don’t want to receive irrelevant and impersonal messages, research completed by Internet Retailer (2015) found that shoppers want marketing tailored to their preferences therefore it is crucial for brands to invest in AI technology in order to get personalisation right.
- Subject Lines and Copy
AI can be used to determine the most successful subject lines, copy and calls to action that individuals are most likely to respond to. Subject lines have a strong influence on open rates of emails (Balakrishnan and Parekh, 2014). According to Phrasee (2018) an AI marketing company, AI generated subject lines and copy, outperform human written equivalents 95% of the time. AI technology can learn what arrangement of content will perform best for each customer. This technology is designed to sound like a human and be consistent with the brand image, so the customer will still feel as if they are getting that human touch.
Take a look at Phrasee’s website to see how the technology works:
https://phrasee.co/how-it-works/
- Frequency and Send Times
It is common for marketers to assume what the best time of the day is to send out a mass email offer, but it is rarely the case that one-time suits all. Every individual has different timings and habits of checking their emails. AI offers a much better approach. By analysing all different segments and individuals, machine learning makes it possible to learn when each recipient is most likely to open their email and tailor the send time to their exact need to maximise the open and conversion rate. It works the same way with frequency, some customers may react well to receiving multiple emails, whereas others only want to receive one a week and may unsubscribe if their inbox is filled with more than that. Zhang, Kumar and Cosguner (2017) found that companies who send emails too frequently can drive customers away. AI can predict what works best for what customer.
Watch this short video that explains machine learning:
https://www.youtube.com/watch?v=mJeNghZXtMo
- Real Time Data
Using real time data can elevate your emails and make them extremely relevant for your customer. Live weather feeds, social listening into trending topics, looking at numbers of people looking at certain offers, these can all be used to a brands advantage, for example: the recent snow in the UK could trigger certain retail brands to send out personalised emails, depending on the consumers location, encouraging them to buy a new coat, boots, or de-icer that is on offer. Personalised predictive marketing like this can be extremely relevant and valuable. Artun (2015) says that predictive marketing creates more relevant and meaningful experiences therefore boosting customer loyalty and revenues.
Read this article on real time data and how it can benefit a brands marketing:
- Promotions
Different people react differently to different promotions. Some might only click a link when it says: ‘20% off for students’, whereas others might only click when it says: ‘Free Shipping’. Revenue opportunities can be missed when brands send their subscribers the wrong promotion. Artificial intelligence can enable brands to collect significant amounts of data about an individual’s previous purchases, clicks, wish lists and page views and then tailor which offers will perform best for each customer. It would take a lifetime for a human to analyse that amount of data and AI offers accurate results.
Read this short article on AI Email Marketing:
https://martech.zone/marketing-email-artificial-intelligence/
- Analytics
Email campaigns generate a lot of data, this can be massively useful for future campaigns and analysing this data is invaluable for brands to get to know their customer on a deeper level, and in knowing what works and what doesn’t, and not just necessarily in emails. AI can help measure impact and give more in depth insight than just counting your open rate and CTR. The data that is evaluated can be used to benefit other channels, to add to the entire omni-channel experience for a consumer. If you know your customer doesn’t respond to product recommendation emails, then don’t send them notifications for the same thing on your app. Gupta and Jhunjhunwala (2016) says that analysing this big data using technology can give you a 360 degree view of your customer and this is invaluable.
Check out this Campaign Monitor article about using data to drive your campaigns: https://www.campaignmonitor.com/blog/email-marketing/2017/06/how-to-use-data-to-drive-email-marketing/
If you’re interested in Artificial Intelligence and how it might effect our lives in the future, take a look at this TED talk: https://www.youtube.com/watch?v=BfDQNrVphLQ
References
Artun, O. (2015). Predictive Marketing [electronic resource] : Easy Ways Every Marketer Can Use Customer Analytics and Big Data. Wiley, pp.3-4.
Balakrishnan, R. and Parekh, R. (2014). Learning to Predict Subject-Line Opens for Large-Scale Email Marketing. IEEE, p.579.
Email Marketing Industry Census 2017. (2017). [online] Econsultancy. Available at: https://econsultancy.com/reports/email-census [Accessed 1 Apr. 2018].
Gupta, A. & Jhunjhunwala, K. 2016, “Analysing brand sentiment with social media and open source Big Data tools“, Journal of Digital & Social Media Marketing, vol. 3, no. 4, pp. 338-347.
Internet Retailer. (2015). Shoppers want marketing e-mails tailored to their preferences. [online] Available at: https://www.digitalcommerce360.com/2015/01/08/shoppers-want-marketing-e-mails-tailored-their-preferences/ [Accessed 6 Apr. 2018].
Marketer Email Tracker 2018. (2018). [online] DMA. Available at: https://dma.org.uk/research/marketer-email-tracker-2018 [Accessed 4 Apr. 2018].
Phrasee. (2018). The Benefits of Marketing Automation with Phrasee. [online] Available at: https://phrasee.co/benefits/ [Accessed 6 Apr. 2018].
Zhang, X., Kumar, V. and Cosguner, K. (2017). Dynamically Managing a Profitable Email Marketing Program. Journal of Marketing Research, 54(6), pp.851-866.