Once upon a time, a graphically appealing website, some SEO, some investments in ADS campaigns and newsletter mailings were enough to attract visitors to a brand’s digital properties and boost its online presence.
But today, with around 2 billion websites and about 567,000 new ones every day, the picture has definitely changed. Increased competitiveness, rising acquisition costs, the growth of the eCommerce sector and increasingly demanding consumers eager for personalised shopping experiences and brand interactions have caused the focus of brands and companies to shift to this front.
Personalisation of the customer experience has thus become a determining factor and the website, one of the first touchpoints of the customer journey in which to invest.
Website Personalisation: the advantage of an I.A.-based strategy
Content, messages, products and much more: a strategy for personalising a user’s online browsing and purchasing experience involves multiple aspects.
The ultimate goal remains that of creating a website ‘tailored’ to each individual user who accesses it, which translates for the brand into the possibility of offering engaging experiences and interactions, with significant returns in terms of loyalty and retention.
More content and a website/shop that adapts to users’ behaviour: in a website personalisation strategy, artificial intelligence and machine learning are two crucial aspects as they allow the personalisation of the customer experience to be set in a real-time context.
From data analysis and dynamic segmentation to the delivery of personalised content and messages, artificial intelligence and machine learning algorithms are able to regulate every step of the process.
Advanced profiling and dynamic segmentation: the first step for a successful real-time personalisation strategy
As can be easily guessed, at the basis of a successful real-time personalisation strategy is an effective profiling and segmentation of one’s audience.
Demographic data, information on navigation and/or purchase paths, data on interests, passions, needs are fundamental to clustering users and showing them ‘tailor-made’ content.
Blendee’s Marketing Operating System makes it possible to collect and normalise data from multiple channels and sources and thus create complete unified customer views, updated in real-time.
At the heart of this is a process of identity resolution that makes it possible to know, but above all, recognise each individual user and customer, in real time, thanks to the convergence and ‘resolution’ of the different IDs attributed during the different interactions in the various channels and touchpoints..
The result? The user is offered, both on-line and off-line, the right product or content at the right time, engaging them with personalised messages and communications, while fully respecting their privacy.
But, what data and information can be collected and used for dynamic segmentation activities?
Let us try to analyse them in detail:
- biographical information that allows us to carry out basic clustering, e.g. based on gender, age, profession
- geographical or location data: this allows us to understand from which geographical area a user connects;
- device data: it is interesting to understand whether a user surfs more from desktop or mobile;
- traffic sources and source campaigns: understanding from which source or campaign the user lands is crucial to creating consistent browsing experiences;
- browsing or purchasing behaviour information: this is information collected on pages and/or categories viewed, products added to the shopping cart, products purchased;
- customer journey data: are we looking at a new, newly registered user or a loyal customer who has made a recent purchase? All this information is useful for creating a valuable user experience;
- information from CRM or other systems: in this case the data collected is very precise and often provided directly by users;
- data collected through surveys, profiling forms: this data is difficult to deduce from the analysis of the user’s purchasing behaviour alone.
Real-Time Personalisation: the value of Blendee
Real-time personalisation is a highly effective strategy to engage users and improve performance in terms of revenue and retention, but the right technology solution is needed to implement it.
All this seems even more relevant in the face of the much announced deprecation of third-party cookies, which brings the focus back to the need to deploy privacy-compliant data-driven strategies.
Data collection, data normalisation, advanced profiling, audience enrichment and extension, but that’s not all: Blendee makes it possible to make the most of all the value of the data collected in order to deploy truly winning real-time personalisation activities.
Thus, let us briefly review the key engines and features that Blendee offers in the field of real-time personalisation.
BEHAVIOURAL MESSAGES
The “Behavioural Message” engine is one of the fundamental pillars in the context of web personalisation, as it allows the user’s browsing experience to be personalised in real-time with messages and communications aimed at increasing user engagement.
The right message, at the right time, to the right person: Blendee allows you to configure a behavioural message in a few simple steps
RECOMMENDATION ENGINE
Blendee’s Recommendation Engine allows you to create product and content recommendations to be integrated into the most salient sections of your website or shop.
Content and product recommendations are, in fact, one of the most salient aspects when it comes to on-site personalisation. In both eCommerce and lead generation, showing the user products and/or content in line with the user’s expectations and interests is a critical success factor in terms of engagement.
SMART SEARCH
Blendee’s “Smart Search” engine makes it possible to personalise search results, showing content and products more in line with the user’s expectations or segment. At the personalisation level, the ‘Smart Search’ engine allows you to work essentially on two levels, that of contents/products to be shown and that of segments. Based on this second level, it is possible to link the display of products to the segment to which the user belongs.
FORM E SURVEY
The “Form & Survey” engine is particularly useful for use not only in lead generation and lead nurturing, but also in eCommerce. It makes it possible to create dynamic smart forms aimed at collecting data and information that is difficult to deduce from the simple observation of a user’s behaviour.
In most cases, in fact, the most interesting information is obtained by asking users more or less direct questions.
The success of a brand is increasingly linked to its ability to intercept the needs of consumers, engaging them with personalised and valuable experiences.
Real-time personalisation thus becomes key to connecting with customers and improving conversions Faced with a consumer that evolves and changes over time, artificial intelligence and machine learning are revolutionising this space, enabling brands and companies to offer increasingly personalised and relevant experiences.
