Bidaway

BidAway is a website part of the hospitality industry featuring a bidding model.

The site offers a wide range of travel and activity packages through exclusive partnerships.

THE CHALLENGE

Potential customers were visiting the BidAway website but participation in the actual bidding process was too low.

In many cases, rather than leaving a room empty, hotels will prefer to sell rooms at a reduced rate - even opting for the customer to decide the price. Taking advantage of this, BidAway is a website that uses an auction process for a chance to win a reduced fare. Alternatively, if users prefer not to participate in the bidding process, the site allows for them to buy and book directly at a competitive price.

The Analysis

Prior to selecting the design method, we performed a standard SWOT Analysis (Strengths, Weaknesses, Opportunities and Threats) to see how BidAway compared to their competitors. We found that the website already had an attractive aesthetic that was strong in communicating the high-end services that their target audience demands.

With the BidAway functionality and infrastructure already strong, we wanted to determine where the best area to invest would be. We decided to use Kano Analysis, a research method that measures emotional reactions to individual features of a system.

The Method

With Kano Analysis we would be able to answer strategic questions regarding the features that have the highest satisfaction

Through the SWOT Analysis we were able to identify 28 important website features from which we chose 12 to be the main focus of our research. As Kano Analysis requires personal interviews with potential users, for each of the 12 features we created a sketch that would aid us in explaining to the participants how each feature works. During the sessions a predefined three-question survey was applied for each of the features tested:

  1. How would you feel if this feature was present?
  2. How would you feel if this feature was NOT present?
  3. How important this feature is to you?
Questions 1 and 2 were answered with one of five options:
  • It must be that way
  • I like it
  • I’m neutral
  • I can tolerate it
  • I dislike it

Question 3 was answered on a scale of 1 (not important) thru 10 (extremely important).

The interview data was input into the CS (Customer Satisfaction) Coefficient formulas to determine both the satisfaction and dissatisfaction coefficients of each feature. The coefficients were then plotted onto a Satisfaction Coefficient Matrix as well as a Double Rank Visualization.

Finally, the participants were divided into three categories 1) Early Adopter 2) Late Adopter and 3) Non Adopter. The results were also analyzed using the matrix and rank visualization.

The UX Findings

The Satisfaction Coefficient Matrix revealed:
  1. Direct Booking was a feature that would build trust among BidAway’s users. As a one-dimensional feature, the more it is refined the more satisfaction it will bring.
  2. Facility Details, Ratings and Full Mobile Version are important to users: they are key to developing the perception of quality service.
  3. Travel Inspiration and Packages are non-expected attributes. They were attractive but perceived as a novelty.
  4. Refined Search is relatively important as well. It could be a great market differentiator for BidAway and is also perceived as a quality enhancer.
The Double Rank Visualization revealed:
  1. The absence of Travel Inspiration and Packages would cause very little dissatisfaction but its presence would increase the satisfaction potential dramatically.
  2. Likewise, providing users with the opportunity to do a Refined Search and Browse by Theme would also cause significant satisfaction but its absence would not disappoint.
  3. Bid at Auctions, Social Reviews and Deal Alerts are also opportunity areas.
The Adopter Comparison revealed:
  1. Packages, Direct Booking and Travel Inspiration were among the main concerns for all three adopter subgroups.

The UI Solutions

Analysis confirmed that Packages and Direct Booking were promising features for BidAway.

One of the main purposes behind the Kano Method is to identify where new concept creation could be most beneficial. Travel Inspiration came out on top as the feature that was not yet supported by BidAway but should be.

We created a straightforward and functional mock-up for the proposed Travel Inspiration feature that would function as the landing page for BidAway.  Customers would be inspired with just three simple steps:

  1. What You Like – A variety of images and options that fit your vacation style. Options range from Beaches and Sun, to Adventure, to Museums and History.
  2. Where You Want to Go – Select how close or far from home you are wanting to go with options ranging from the Caribbean to Africa to the South Pacific.
  3. Finally, with a click on the “Inspire Me” button customers are presented with the bidding options that best fit with their desires.

With addition of Travel Inspiration at the very start, customers will not be overwhelmed by the bidding process, but rather, be guided into the bidding process with ease and excitement.

The Takes Aways

Taking the time to apply a quantitative research method enables you to validate your assumptions about certain features and how they make users feel. The findings are oftentimes surprising and are always valuable.

The results from Kano Analysis are data-driven insights that are validated with statistical confidence. They disclose the level of satisfaction a feature would trigger among users. This quantitative framework can be used to guide the next marketing strategy.

The data generated is a powerful tool to communicate and evaluate the Return of Investment (in terms of user satisfaction) for improving existing features and for creating new ones.

Distribute your budget, time and resources: every project has its own needs, restrictions and set of design development resources available. Research results are not final in the sense that they’re not an exact recipe to follow. Rather, results point to and inspire the decision-making for the next design iteration. Ultimately, it is up to stakeholders to decide the next move based on the information that’s presented.

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