How to create a personalised shopping experience to improve user journey UX Case Study

Business Objective

To know the customer, to gain their trust, and to sell more effectively to them.

User Objective

To explore the app/website without any restrictions and based on my personal preferences.

Problem Statement

As a service provider I need customer’s personal information like age, gender, date of birth, location to provide them personalised experience. But users don’t feel secure or confident while providing their personal information because that is obviously personal and they step out from the app/website. How can we get the personal information from our users to provide them personalised experience.

User Persona

Alok Mittal
Age 28 
Educated
Working
Lives in Delhi (Tier 1)
Loves video games and online shopping

Needs

  1. He wants to explore new apps/websites.
  2. To shop products online.
  3. Wants to save time and effort by avoiding filling long form.
  4. Wants to view products on the basis of personal needs.

Pain Points

  1. Whenever he open any app/website he has to sign up.
  2. It takes lots of time and effort to fill forms.
  3. App/websites suggestions are not relevant for him.
  4. He doesn’t feel safe and secure while sharing his personal information.

Insights from the research

For many retailers Personalisation is likely to become a key focus in 2018. Firstly it represents an opportunity for retailers to empower better customer experiences, and secondly, increased revenue with a service that adds that ‘human touch’ to the customer journey and lets her know “we’re listening to you”.

Companies that truly help you, don’t bug you with stuff you don’t need and tailor to your personal needs. Creating personalised shopping experiences reduces the search costs for consumers as we only show customers garments that suit their shape and style, instilling confidence in the purchases made.

Market Research

1) Tinder

Tinder uses Facebook profiles to authenticate real people and keep what the app believes is “quality control” to the highest possible level. It also uses your Facebook profile to match you up with people of similar interests and your Facebook likes as well as finding your location.

2) Amazon

Amazon has a huge data analyzing system in place which can take your browsing history and predict what you may be interested in looking next. How does it do that? It analyzes “pattern” of behavior and “predicts” what you may need next. For example it noticed that every month you are buying a particular water filter for your Kenmore refrigerator (making this up). Based on history it can then do the following.

  1. Towards the end of the month it can suggest it is time to re-order the same filter
  2. Offer you a filter from the competitor brand (assuming the competitor paid them to do product placement) and suggest it first than your prefer brand
  3. Provide a suggestion to buy a new refrigerator which does not use filter at all

Typically a decision tree is traversed to come to above suggestions based on history of many months and sometimes years.

3) Airbnb

Airbnb’s onboarding flow starts out strong with a series of full-screen forms. Five screens might seem like overkill for a simple account creation, but because the screens contain only one question, each step is easier to digest.

The conversational language also helps ease users along. The copy on screen two and screen three flow together like a conversation: “What’s your name? And, your email.” This makes the process feel less like a generic form.

Once onboarding is complete, the app drops us onto the main screen. The “For You” tab displays experiences prominently, encouraging users to browse Airbnb’s non-housing listings. The company now catalogs local experiences and tours in addition to homes, so this is a good way to encourage users to explore new parts of the app.

Information we need from user

  1. Name to give personal touch
  2. Age to show products according to that age group
  3. Gender to show products from that gender section
  4. Profile picture for 3d try on
  5. State to know the user demographic
  6. Preferences means Electronics, Footwear, clothing for more accurate results
  7. Buying habits means app user/website user, regular customer/one time customer, shops yearly/monthly to provide the offers and discounts according to these basis

Solution 1 (Connect with Facebook/Gmail)

Nowadays, to let us know about the user and to verify them Connect with Facebook and Connect with Gmail is one of the best way available. It reduces the time and effort to fill the long form and user can avoid painful signup process. And according to the research mobile users show less interest in typing than web users. Let’s discuss each scenerio

  1. When the user tap on “Connect with facebook” it will redirect them to facebook login page(if not logged in) and ask the user to access info shared publicly. In this way system will get user name, profile picture, age, gender, location, email.
  2. Then the second option is connect with gmail. When the user tap on “Connect with Gmail” button it will redirect them to gmail login page(if not logged in) and after successful connect with gmail system will get information like name, age, gender, state, profile picture (if uploaded).
  3. Third option is sign in via email. This is a typical way of sign in process used in most of the apps. User has to enter their Email Address and password to sign in into the application.
  4. And the last and least prior option is “Skip”. We are not forcing our user to login into the application to view products available. We want to provide a friendly user experience and we want to build a relationship. So we will provide the time to our user to build trust in us.

Solution 2 (Personalised experience by using browsing history)

In this solution we are using browsing history of our users to show offers and products based on that. Like, if you are looking for a ceiling fan and search it frequently on web browser/app. Website/app will start showing you Ceiling fan to initiate a trigger to purchase them. System will check the buying habits of the user and will recommend products on that basis. In this solution we are not forcing our user to login into the application to have personalised experience. And we can directly redirect the user from splash to home screen. In this way we can save the time and effort of our user.

But to show accurate results system will take time to collect the data which can vary from a month to an year.

Solution 3 (Conversational Signup)

In this method we will ask the information directly from the user but in a friendly way. Research says that people avoid filling long forms. And the positive conversion rate are higher when we divide the difficult task in chunks. So, I divided the form in 5 steps. I started from the most basic information “name” of the user then gender, email and password. We asked most relevant information during sign up and in the next step I asked less relevant information which can be skipped by user.

The initial onboarding process is painless. However, one solution that might help users speed through it is a progress bar. By allowing users to see how much longer they have left in the onboarding process, We can motivate users who drop off early in the funnel. A quick A/B test is an easy way to see if this solution provides value.

Most importantly, no matter how confident or not a customer may be, Personalisation inspires — it adds that element of fun to the user experience whether it’s through curated and personalised homepages and weekly style emails or simply through a spot-on style recommendation with a fashion twist.

Conclusion

I hope it gave you a little insight into the decisions I made. It was a really interesting task and I thoroughly enjoyed working and researching for it. I have also taken a bit of liberty to add my suggestions and couple of new features. Hope I was able to add some value to the assignment.

Let me know what you think! Bye!

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Cheers!!