How Big Data Insights Can Help Fitbit Win the Fitness Category Back

Fitbit had a tough time maintaining its status quo as the category leader in fitness trackers and overall wearables in 2017. Falling to the third place for the first time in the first quarter of 2017, between Chinese gadget maker Xiaomi and Apple, what the fitness brand could do with is a little introspection. Product pricing and timing impacts, not just the sales, but also its visibility at an online store. Working on this factor can help Fitbit elbow out the competition, all with the right data.

We have focused on a particular product: Fitbit Charge 2 to illustrate what accurate Big Data insights can do for the brand.

Using our analytics, Fitbit can study in detail about the e-commerce stores from segregated geographies across the world that are selling their product. Retail can deliver a live comparative analysis of the prices-ensuring that their merchandising teams can quickly adopt optimum margins and maximize sales revenue.

Building A Deeper Insight Into Global Competition

Fitbit Charge 2 is sold not just by sports apparel and fitness stores, but also by multi-brand e-commerce giants. A large chunk of Fitbit sales in for each region come from Amazon.com (USA), Flipkart (India), Target (Canada), Currys (UK), PC World (UK) and Tokopedia (Indonesia).

By studying these retailers, Fitbit manufacturers can have a clearer idea of where the product stands in the current market.

Real-Time Updates In Data

A dashboard screenshot of the product pages reveals where the Fitbit Charge 2 is up for sale. With the Compare & Analyse module of Incompetitor ™ manufacturers can do a comparative study of FitBit Charge 2 pricing over time.

This gives a broader picture, enabling Fitbit to stay up-to-date with the changes and create successful marketing strategies for the future. It makes global price comparison for Fitbit Charge 2 a matter of a few clicks and couple of seconds.

By going through the single view USD currency chart, it is learnt that the prices have been constant for Curry’s (UK) and variable for Flipkart (India), while Target (USA) sells the product at a minimum price.

Relationship Between Price And Visibility — Price Sensitivity

Let’s take into consideration the price vs time and visibility vs time graphs for Flipkart. It is observed that there is an inverse relationship between prices and visibility. For instance, from August 2015 to September 2015, when the prices increased, the visibility of the product declined in comparison to its competitors and it also means that this product is price sensitive.

This metric allows FitBit Charge 2 manufacturers deploy a specific pricing strategy for a particular online store. The brand can define custom prizing rules which are meant specifically for the product, and auto-generate smart prices that always competitive while pushing maximum margins.

Let us take another example. As far as Target is concerned, there is a huge fluctuation in the visibility for September 2015, even while the product price remained constant. This could have been related to the release of the Apple Watch this year.

Huge differences between the pricing of the Apple watch and the Fitbit Charge 2 can ensure the gradual increase in the visibility of FitBit Charge 2.

An Insight Into Consumer Preferences Based On Geographic Location

A detailed insight into consumer preferences based on the consumer’s geographic location allows for decisive assortment planning. For instance, Curry’s sales charts show that the teal blue colour for Fitbit Charge 2 is the most preferred colour in the UK market.

Using Data To Deploy Better Marketing Strategies

Fitbit Charge 2 manufacturers can use retail data analytics to get real-time insights to revise their product release strategies, helping them make better marketing decisions combined with intelligent pricing strategies.

We’ll be up looking at the data while you’re chasing bigger targets. Optimize your retail business and always stay ready for the New Age Shoppers. Request a Demo!

Originally published at https://www.intelligencenode.com on December 18, 2017.

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