Successful hyperpersonalization with the right data strategy
First-class brand experiences and customized offers at exactly the right time? That's what most customers want. To make this happen, companies are turning to hyperpersonalization. The strategy includes individual customer approaches and highly personalized offers, and relies heavily on extensive and detailed customer data.
But be careful: two out of three respondents are skeptical about the way companies use their data in marketing (Ipsos / Google, 2021). Learn how to protect your customers' privacy, increase their trust and successfully implement hyperpersonalized marketing measures with the right data strategy.
The most important aspects in brief
- Hyperpersonalized marketing measures promise customized and highly relevant customer experiences, thereby promoting loyalty to the company.
- Proper collection and storage of real-time and behavioral data is a key factor in the long-term success of hyperpersonalization.
- Customer data platforms and artificial intelligence support companies in their customer-first data strategy.
How companies benefit from hyperpersonalized marketing
Customer-oriented, personalized marketing is nothing new per se and has already proven successful. Regular or standard personalization relies on personas and basic customer data such as names, locations and other geographic and socio-demographic characteristics. Based on this general information, customer segmentation is performed with the aim of making marketing campaigns more relevant to specific target groups. In contrast, hyperpersonalization goes a step further, creating more precise and personalized customer experiences through the use of real-time and behavioral data.
The benefits of hyperpersonalized campaigns speak for themselves: targeting the personal preferences and needs of individual customers enables a more specific approach with highly relevant content. These customized offers not only influence the purchase decision, they also offer potential for upselling and cross-selling, thereby increasing profitability. Positive buying experiences ultimately lead to strong brand allegiance and customer loyalty, and have an overall beneficial effect on the interaction of (potential) customers with your company.
In the long run, successful hyperpersonalization for companies is reflected in reduced marketing costs, optimized ROI and maximization of overall revenue.
Clear commitment from the young target group: More than half of millennials and Gen Z are willing to trade their data for personalization – most likely because they recognize the benefits that personalized offers provide them (Ipsos, 2020).
Most companies are already aware of the benefits of hyperpersonalized marketing strategies, but the proper handling of the customer data required for this purpose presents a challenge for many. Changing data protection requirements and growing doubts about the trustworthy use of data by companies require a secure, efficient data strategy for future hyperpersonalization measures.
Hyperpersonalization and data protection
Customer data is the basis for every personalized marketing measure. In addition to information such as name, age, location etc, hyperpersonalization is characterized in particular by the use of real-time and behavioral data. These larger, more complex data volumes include, for example, browsing activities or data regarding the actual purchasing behavior of customers.
With the elimination of third-party cookies and increasing criticism of obscure data collection strategies, the question is how this data will be collected in the future and how hyperpersonalization can be reconciled with maintaining the privacy of your clientele. Because: 53% of users find personalized ads more disconcerting than helpful when it appears that their mobile devices are listening to them (Deloitte, 2022).
To ensure that your hyperpersonalized campaigns achieve success and are not met with mistrust, a customer-first data strategy is recommended for data collection. Here, questionable data collection measures such as geo-tracking or active wiretapping are dispensed with, and transparency and customer trust are given priority. Only the data required for a specific purpose is collected and is not resold to third parties.
First-party or zero-party data is conceivable at this point. The former is first-hand data, meaning it is acquired when customers interact with your online store or website and not through partners or cookies. Zero-party data is an innovative data collection strategy in which the key factor is its voluntary nature. Here, customers are actively asked for information after completing a purchase, for example, and only data that they knowingly share with a company is stored.
Transparency is critical to a willingness to share data: Users are three times more likely to respond positively to advertising and twice as likely to consider it relevant if they feel they have control over how their data is used online (Ipsos / Google, 2021).
Checklist: with this data strategy, hyperpersonalized marketing measures succeed
In order to successfully implement hyperpersonalized marketing, the right data strategy is the be-all and end-all. This includes not only identifying and collecting all the data necessary for the success of a campaign, but also storing it securely and making it usable efficiently.
The following real-time and behavioral data are relevant to hyperpersonalized services:
- Active times, i.e. times when a customer logs in or time spans when they make online purchases;
- Browsing activity of the customer;
- Triggers that lead to greater involvement;
- Customer's affinity for discounts, special promotions, free templates etc;
- Data about the actual purchasing behavior.
Once the right customer data has been identified, it's a matter of collecting, storing and analyzing it in a way that complies with data protection regulations. Customer data platforms and CRM systems in particular can provide support here. They bundle all customer data from all channels in a central location so that it can be used for a targeted customer approach.
Artificial intelligence is also being used in hyperpersonalized marketing strategies. BSI AI helps you analyze the collected data and create customer clusters. In addition, AI provides recommendations for your marketing, allowing you to create highly personalized and individualized customer experiences in real time.
With the right tools, relevant customer data can be confidently and correctly captured in line with a customer-first data strategy and successfully used as the basis for your hyperpersonalization measures.
Conclusion: outstanding customer experiences thanks to data-driven hyperpersonalization
With hyperpersonalized offers, companies can successfully upsell and cross-sell, maximize customer value and promote customer loyalty. Customer data plays a crucial role in the creation of such individual and relevant campaigns. The right data strategy ensures that you collect this data securely and in compliance with data protection laws, and that your customers reward you with positive purchasing decisions and long-term brand allegiance!
Not sure where to start with hyperpersonalization and what tools are useful for properly handling customer data? At BSI, we work with you to analyze your situation – so you're provided with the exact solutions that support your marketing goals. We're looking forward to hearing from you!