Technologies like artificial intelligence (AI) and machine learning are transforming marketing: marketers can now understand and target their customers to an unprecedented degree. AI is not only automating some of the most mundane and time-consuming processes, but also solving the once unsolvable issue of how to turn terabytes of customer-generated interactions into valuable insights. For marketers, these insights are enabling relevant and personalised experiences for each customer.
But whilst marketers can now meet their audience’s personalisation demands, they face the challenge of how to balance the use of customers’ data without encroaching on their privacy. Data unlocks incredible insights but if marketers fly too close to the sun, they stand to lose the loyalty and wallet-share of the customer-base that they worked so hard to obtain.
The impact of digital transformation on personalisation
Personalisation is nothing new; from the dawn of modern consumerism offering a personal touch was a key differentiator for high-quality organisations and service providers keen to set themselves apart from the rest. Remembering client names, previous purchases or children’s birthdays added that ‘je ne sais quoi’ that bonded business to its customers. It fostered loyalty, repeat business and positive word of mouth marketing. But it was time-consuming and often inaccurate.
Then came AI and machine learning, which enabled businesses to communicate at volumes never before considered possible. This insatiable appetite for reaching vast potential new audiences quickly led to a boom in mass marketing techniques like email send-outs. In later years the addressee name would be changed which, at the time, was considered revolutionary but the notion of personalisation was nowhere near the top of the priority list. Today, we’ve come full circle only now personalisation is no longer the preserve of the premium businesses.
With sophisticated personalisation now the norm, customers expect communications and products tailored to their individual preferences, which is being driven by skyrocketing expectations and advances in technology. According to an Accenture study, over 75% of consumers are more likely to purchase from retailers that know their name and purchase history and provide recommendations that are appropriately on-taste. And 52% are more inclined to change brands if a company doesn't offer personalised communication. We mustn’t forget that post-GDPR, consumers also understand how valuable their data is so they have higher expectations of how businesses use it.
AI enables marketers to identify their audience and tailor experiences, content, and delivery – ultimately driving better conversions and marketing ROI. And crucially, AI helps marketers to achieve hyper-personalisation.
How data can foster long-lasting relationships with consumers
Using AI to serve relevant content is also a prerequisite to marketers building long-lasting relationships with their audience. As businesses strive to exceed customers’ expectations, they raise the bar higher for all marketing departments and unwittingly make consumers less forgiving of poor interactions and engagement. Research shows that 54% of people will only tolerate two to three negative experiences before they abandon a brand altogether, whilst 1 in 5 will abandon a brand after only one bad experience*. Conversely, research also shows that 91% of consumers are more likely to shop with brands that recognise, remember, and provide them with relevant offers and recommendations. Put simply: brands must foster long-term relationships by ensuring they get the message and context right across all channels, whether it’s email, social, physical or online.
But marketers must also consider the implications of misusing customer data. Being able to build personalised content to engage effectively with each individual customer is of great use for any organisation. However, doing it without defining clear business goals or without having a clear understanding of how personal data is collected and used, can frustrate customers and ultimately make them hate you.
Balancing personalisation and privacy with relevance
It’s essential to balance privacy with relevance to avoid scaring and annoying customers to the point they feel uneasy and switch off from the brand’s communications. And the repercussions extend way beyond losing a customer; misusing data could see an organisation incur devastating GDPR fines and a damaged reputation.
There are some simple steps businesses can take to avoid this. AI engines handle the journey to design and product recommendations, but marketers are responsible for keeping these interactions beneath stalker levels. Marketers must think carefully about how relevant and timely automated triggers are and use take advantage of the technologies which facilitate send-time optimisation for marketing messages.
Brands should enlist AI to translate customer intelligence into relevant offers. Most consumers will “ghost” a brand that sends too many irrelevant offers. Let AI engines crunch real-time data from universal consumer profiles into on-taste, situational offers that are highly targeted.
Finally, businesses should ensure they use clean, reliable data. AI is only as “intelligent” as the data you feed it. Misspelt names, incorrect genders or addresses scare off customers forever. As the antidote, marketers are connecting their AI engines to customer data platforms (CDPs) that verify and integrate data across departments and touchpoints.
Ultimately, marketers need to keep carefully balancing personalisation with privacy to succeed by carefully focusing on the customer experience and using technology to foster a long-term relationship built on trust and understanding. Get it right, and the rewards of fostering profitable long-lasting relationships with consumers are immense.
Written by Tim Stone, global head of revenue marketing, Selligent Marketing Cloud
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