Banners, announcements, emails and new trends. From personalized advertising to other strategies: the advantages of a brand
You’ve never seen it before, but as soon as you’ve bought that new pole, your brand starts to appear everywhere, almost haunting you. In the offline world this phenomenon is labeled as a Baader-Meinhof effect . In essence, our brain begins to notice something that previously neglected (the brand in fact) and processes it as a coincidence. Online , on the other hand, things change: the era we live in is that of customer analysis , a continuum targeting / re-targeting . Basically, we visualize a content on a site (an advertisement) and then it appears everywhere. It’s digital marketing , beauty! It works like this.
Trademarks, data and algorithms
What fuels every customer analysis promoted by companies? The whole digital marketing world is based on a continuous collection of behavioral data , analysis and sophisticated algorithms to re-target . Yes, there is no space for coincidences. This new era has profoundly changed consumer behavior and expectations: but how? It’s still: Which strategies help companies to excel in the new era of customer analysis?
The analysis of consumer needs are the major advantage of every online business system. In fact, the latest research on the topic shows a strong correlation between two operational levels:
- the ability of a company to exploit data analysis;
- and creating new value for customers in every touchpoint.
On the whole, it is now understood that consumers want personalized interactions . Basically, they expect a brand to predict what type of film it may interest them, or suggest which shirt to match the jacket they have just bought. Users have now developed very high demands , distributed in short intervals of attention . And the work of analysis has become progressively complicated.
Users … bordeline
Today, it is not easy to analyze consumer behavior: they let themselves be carried away by sensations , we could say. They constantly change their preferences, block advertisements, jump from one device to another and leave the apps they do not use. But this does not change their expectations: they pretend that brands recognize them , and this regardless of where they are. Moreover, the options have multiplied; so why not choose?
In another White Rabbit blog article we had already addressed this specific topic, and in the light of one of the latest research launched by Google. Here, however, we will focus on the analytical difficulties related to data collection . We will also see some reasons that can really make the difference.
Data and profiles
A current problem concerns data fragmentation . The same dilemma exists for the fragmentation of profiles . A trivial example: we started to follow the YOOX brand on Instagram because it has struck us, but it lacks our like on Facebook . And many other contexts of this kind.
The question to ask is the following: how do the best companies behave in the face of this marked fragmentation? Modern customer analysis solutions allow all these data to be combined into a single overview . It is a matter of keeping together some flows of information and analyzing them in a unitary and coherent manner, individually or in aggregate. These data collections show:
- who are the customers;
- where they are (generally) during their purchase journey;
- what do they want;
- how they act in reference to the various connection devices;
- (and therefore) which marketing strategies can be more incisive.
It is a set of information that allows us to improve the Customer Experience , personalize content, develop more appealing websites and apps and, naturally, increase profits. Basically, a good analysis of the customers determines an advantage in terms of business and therefore of competition with the other brands.
In this sense, the road to follow seems to be outlined: many are focusing on artificial intelligence (AI). But the automation of data collection and subsequent customer analysis is still a hot topic, despite being an advanced sector. Procedures that work from a large amount of data often do not yield the same results for those systems that require clear, structured data from a variety of sources.
In reality, learning algorithms automatic are taking giant steps. For example, today they are able to simplify the access and classification of unstructured data of large companies. And they answer questions that are still surprising, such as
- why some customers are more sensitive to some offers and others are not?
- where do they look and why do they download some apps and not others?
- Which communication channels is best to use and for which users?
- what could be the best time to send a commercial offer?
In this sense, we can already distinguish between predictive analyzes and analyzes carried out in real time . Both improve the campaigns, because they help us to customize the offer, predict which customers we are about to lose, or “create” new trends that then become real needs.
In short, AI-based automation enables large companies to understand their customers and thus guide them in their choice, developing increasingly optimized experiences.
Customer analysis with White Rabbit
The White Rabbit software has everything necessary for the analysis of customer data:
- Customer Journey statistics (so-called Customer Analytics or Customer Journey Analytics);
- All data on the online relationship (purchases, visits, opening emails, discounts, products purchased, actions on social networks, tickets, etc.) and off-line (telephone calls, meetings, offers) of customers and prospects;
- Clustering of Customers ;
- Marketing Automation on Activities of specific Targets or specific customers;
- Export of the Big Data of the Customer Base and therefore the possibility of using any Data-Mining software to analyze customer information.
- And so on
Use White Rabbit to improve your customer analysis and improve your brand.