For many people, digital reality has permanently changed the way they buy things. With no limitations in accessing offers from different retailers, those who resist this trend are increasingly harder to find. Every day, great numbers of potential customers search the web for information about products and offers they are interested in. Anonymous visitors roam from website to website hoping to come across an offer that is best suited to their needs. How can we attract their interest?
For many years, attempts have been made to address the issue with, for example, recommendation systems. On the basis of stored information and data, these systems suggested products potentially matching the customer’s interest. By analysing customer profiles and historical interactions of individual customers, recommendation systems could align, to a large extent, their suggestions with the recipient’s preferences.
Continuing on this path, organisations aim to improve the efficiency of these systems by placing more emphasis on the identification of significant events positively correlated with the accuracy of generated suggestions. It is the identification of the correct moment that largely helps to achieve the desired result, as demonstrated by case studies of communication and campaigns based on event marketing.
Challenges to effective communication with anonymous visitors to websites and mobile app users seem to be similar to those of identified customers. Two important prerequisites must be met before a correct message can be compiled: A wide profile of data describing the visitor must be available, and the visitor’s interactions must be tracked to identify the best moment to interact. Due to anonymity, the organisation’s internal data cannot be used. So it is necessary to use tracking mechanisms that allow for building such profiles on an ongoing basis with data obtained from digital channels.
Depending on the needs, a wide scope of information can be tracked: from paths taken by a person browsing the website to details provided while completing an online form. By combining data from different days, an increasingly clear profile of the anonymous visitor can be determined. The profile describes the person’s preferences, frequency of visits and engagement level. At the same time, the monitoring of ongoing interactions leads to identification of significant moments that indicate the best time to interact and display feedback.
Identification of abandoned orders is a good example of such activity. At online stores, and also on websites of other service providers – such as telecoms or banks – customers may submit order forms directly on the website. A large proportion of such orders are not finalised, and many of them are abandoned even before completing the contact form. Due to unavailability of contact details, it is impossible to contact customers who started the buying process directly and convince them to finalise their shopping.
The website is a feedback channel that can be used in such situations. A message that encourages customers to return to an abandoned order can be displayed even on the landing page. The shorter the return path, the more chances that the customer will finish the process. Depending on the type of information about preferences and engagement of the visitor, a decision can be made on offering an additional bonus to improve the conversion rate. Such campaigns carried out for customers from different industries have proven that this apparently simple mechanism can also be very effective. Making a reference to an earlier interaction is not a problem, even if the user is anonymous. In addition, the process can be continued rather than restarted.
Interaction monitoring can also facilitate the identification of persons who visit websites or use mobile applications. With the functionality of tracking the details entered into forms, at least an email address or other ID can be obtained and stored in the internal customer’s profile or data warehouse. By linking the ID in the digital space with an internal ID, the displayed content can be even better aligned with individual preferences of each visitor. At the same time, a wider scope of communication channels can be used; not only websites or mobile apps, but also email and telephone. Going back to the abandoned order case, people who are not frequent visitors to the organisation’s communication website can be contacted by call centre consultants.
These issues are addressed by SAS® Customer Intelligence 360. The solution allows for ongoing monitoring of interactions in digital channels, such as websites or mobile apps. The collected data can be used for content personalisation in real time. A wide range of reports and analyses is also available that help you use digital channels and identify moments and sites that may require improvement or support with a campaign.
Transparency of data collection is a very important issue. The ability to track interactions with forms and entered details may raise concerns as to whether data security and privacy are ensured. This is why the key functionalities include the ability to precisely control the scope of collected data and tools for masking and encryption of data. With such controls in place, users can ensure that they collect data in compliance with applicable data collection regulations, and that they collect only such data that is required for the operation of the implemented business processes.
The popularity of digital channels means that companies must be able to address the expectations of a large number of anonymous visitors. A large proportion of decision-making processes related to purchases of products or services occurs before the identity of the other party of the dialogue is known. This is why it is so important to be able to communicate with this segment effectively, seize the opportunity to attract new customers and, consequently, improve sales results.
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