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Customer persona is a conceptual and fictive character of who could be the typical customer. Shorter, it gives us a “realistic” kind of customer (with socioprofessional situation, sex, age, etc …). Of course it’s possible to have several customer persona (like in the Ontela case study). A user persona is a representation of the goals and behavior of a hypothesized group of users.
We are comfortable choosing the young professional, I also consider the parent a viable segment.
The young professional will definitely utilize the service in their business and will see the value to carry over use for personal photos thus increases their usage and dependency of the service (or vice versa). We think given the age group of this persona they will be quick to adapt to the new technology once they commit to using it. Once they commit to using it we believe it will be something that will be difficult for them to give up so they will be a regular customer.
However, we are concerned about the number of potential customer in this persona. We wonder how many 27 year olds are like Steve when he mentions he was “the last of his friends to get up on the latest technology”.
How much do customers in the segment want/need the product/service ?2/53.5/55/5 Most attractive ontela featureeasyUseful-easyFast-easy
Most attractive benefit for the consumerSave precious momentDoing business faster from everywhere to every placeShow pictures Value to Ontela and partners
This kind of people is outdated about technologies, especially in phone domain.
They prefer to stay with their habits because they finally learned how to use it. If they change, the old phone has to be broke (and often, they try to find the same phone or a similar one) or it has to be really easy. Ontele promise their software is easy but we can not say the same about the support (the framework). USA : 10 millionSteve is not a user of new tech but he knows it. Today, we can assume that a young professional of 27yo has to have new tech because it’s really useful for their work (especially for estate agent) and because to have a smartphone gives entertainment.
USA : 10% of 153 million = 15.3 million (actif)Regina is the typical girl of Z generation. The girl who has its own iphone, from a middle class. She is always connected thanks to internet and mobile internet. She is able to better know all new tech that can serve her easier, faster, more usefull.
USA : 20 million
Note:
As we can see, Sarah is not this kind of target who will go on internet to search information (because she doesn’t know really how to use it), and as she has no smartphone with appstore, it’s impossible to target her by this. About specialized magazine, she will be not interested as much. And about specialized TV/radio program, she cans be targeting but it will be a pure hazardous. So it will cost a lot if we decide to touch her, even if the product currently gives a response to her demand. Steve has knowledge in IT and is ready to change its mobile phone. So he will access to appstore, search information on internet, his colluagues already use their cellphones to send pictures. So he will be easy to touch.
Chosen target : Steve, the Young Professional
After the segmentation market, Ontela Pickdeck target will be Steve, the Young Professional. The Ontela Pickdeck’s offer and the Steve’s profile are linked. For us, Steve is the best target.
Steve is 27 years old, he is “cool” and a young active adult desiring to connect with friends. Steve is a “hardworker” who knows the new technology and who uses very often the new technologic communication for his work.
It is a easy target to approach because he needs this type of application to simplify his lifestyle and his work. For Steve, the essential key themes should be “professional” and “easy to use”.
To approach better Steve, we have chosen some promotion supports.
WOM : With all his colleagues and the real estate world. This type of product can change the real estate agent work.
What are the risks of using qualitative personas to select target customer segments? The main risk by using it is that customer personas are just a representation of a typically customer and only linked with the product or the company. It doesn’t care about the geography, sociocultural differences, etc … The other problem is that qualitative personas don’t show the quantity of customer and so the real potential of a group of customer. We cannot know how much “Regina” are in the segment targeted. Shorter, the problem of using qualitative is that it’s just an assumption without quantitative evidences and no descriptives. The firm risks to target their customers only linked with their personas
“There’s no quantitative evidence. The most common pitfall in persona creation occurs when someone asks, “How can you be sure all our users are like the few you talked to?” Qualitative personas are based on the idea that you can talk to a small number of users and see patterns that apply to all of your users. In other words, the risk of being wrong is higher compared to having a large sample size to back you up. If your stakeholders need quantitative evidence to buy into your process, they’ll disregard your personas as a creative but ultimately unreliable tool. Some people simply need the “proof” of hard data. And who can blame them? If you’re going to be making critical business decisions based on these personas, you better be as certain as possible of their accuracy—and be able to persuade others.
Existing assumptions don’t tend to be questioned. You know your business, and you have assumptions about who the users are and what they need. When any person interviews users, he or she inevitably brings those assumptions to the research. The result: People find what they’re looking for. Subconsciously, people look for the things that backup their own assumptions, so that instead of discovering surprises, they simply validate an existing worldview. Too often, their segmentation will look exactly like their original assumptions instead of being affected by the research. It won’t always happen this way, but it’s a serious risk when doing qualitative segmentation.”
Ontella Picdeck Case. (2016, Dec 10). Retrieved from https://studymoose.com/ontella-picdeck-case-essay
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