The massive spread of web fonts means that typography is becoming more and more complex, even on the web. As a developer who is always interested, it is becoming more and more common that you want to know which font has been used. You will also be regularly confronted with this question in the print sector.
In most cases it is provided by the customer. “Take a look at our flyer from last year. We want to use this font in our next project.” The same happens at the Schweizer Online Casino. The client doesn’t know which one it is, of course. The following services know how to help in different ways, but they are the best toolbox currently available…
WhatTheFont is the market leader in font identifiers
WhatTheFont from MyFonts has an advantage in that it has access to one of the largest font collections on the net. And it’s been on the market forever. However, WhatTheFont always relies on images as input and does not offer direct identification on live websites. What sets it apart are the apps for Android and iOS. These allow you to identify fonts with a smartphone camera. Read more here: https://www.entrepreneur.com/topic/web-design
WhatFontis is a useful tool for every web designer. Its use is as simple as bookmarking a page. WhatFontis is available as bookmarklet and as extension for Chrome and Safari. Once activated, it gives detailed insights into the fonts used on a website.
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Do you need an experienced service provider to create your website? Does your website need a technical and content update? Would you like to receive more qualified inquiries from prospects and customers about your website?
The recognition of fonts is always based on an image file. The Chrome extension is basically nothing more than calling the WhatFont-Web-App. The other two extensions put WhatFont into the context menu.
I can’t see an advantage over WhatTheFont. I would only use the service where others have already failed – as last resort, so to speak.
Fount – Bookmarklet with mixed success rate
The competitor Fount is a pure bookmarklet solution, so it offers no extensions or other access to functionality. In comparison, Fount looks a bit old-fashioned, and can’t show correct results with the same reliability. Direct connections to common font libraries are also not available. In my tests Fount did not only reach its limits in many cases, it also worked very unreliably and not in every browser.
Nevertheless Fount is an additional option. But the first tool of choice should not be the service.
The Font Matcherator also works on the basis of images to be uploaded. Its competitive advantage is that the entire font matching portfolio is behind it. So it is similarly strong as WhatTheFont. Fontspring itself sees the Matcherator even further ahead because it can recognize open type features and some other specialties. In my everyday test this did not play a decisive role. The tools were comparably good.
Identifont – This representative of its genre tries to identify fonts by asking the searcher a variety of questions. So you need patience and a basic knowledge to be (possibly) successful.
In the age of progressive individualisation, the following applies more than ever before in customer management: Not all customers are the same. Anyone who wants to be both effective and efficient in addressing customers and really relevant to their target group is obviously not relying on the “shotgun” principle, but is adapting to the different expectations, needs and preferences of specific customer segments.
It therefore requires a precise understanding of customers at an aggregated level in order to identify and respond to relevant patterns without making undue generalisations and overlooking important nuances. Personas have successfully established themselves as a tool for this task, whereby a distinction must be made between two essential approaches:
Already known for a long time in marketing, personas are used as visual “translation” of data-driven segmentation models. Statistical models are the basis for identifying specific groups (segments) with the same characteristics, which at the same time enable significant distinctions between the groups. The aim is to clearly assign all customers/potential customers – in reality, overlaps and a relevant “rest” can rarely be avoided.
In order to make these data models understandable and usable also for non-statisticians, these segments are then “personalized”. The groups are given a name, a face, essential features are highlighted – but at the same time remain fictitious examples of abstract data models. Marketing Personas explain customer behaviour very well, but usually not the “why” behind it.
As part of the Customer Journey Mapping methodology, the development of personas goes the other way round. Typical customer groups are consciously described from a rather subjective perception and attention is paid to factors that are rarely available in data models: Emotions, motivations, needs of the addressees and resulting pain points in the customer relationship – linked to classic socio-demographic characteristics and other data points relevant to the respective business.
Only in further use, of course, is it advisable to validate and qualify assumptions made with the help of existing statistically evaluable data – especially when it comes to ensuring that no relevant customer groups have been forgotten.
In the authors’ view, both of the above approaches are justified and should be used accordingly, depending on the desired business objective. Marketing Personas are generalizing and based on core characteristics, Design Personas are individualizing and specifying.
For companies with a higher level of persona maturity, it is even advisable to break down the silos and integrate both approaches. Coming from active customer management and in line with the basic character of the article, we will focus on personas from a customer-journey perspective in the following and look at them in more detail.