Why You Need Analytics Early in Your Product Lifecycle

With the abundance of analytics solutions available for online businesses, you’d think that we’d have more insights than ever before on how to answer key business questions. But according to Matt Ariker, Chief Operating Officer of the Consumer Marketing Analytics Center at McKinsey, it’s exactly the opposite:

Tremendous insights do exist in Big Data. Companies that use it well are leaping ahead of their competitors. One of the big reasons for that, however, is that they have a very clear sense of what they want to do with all that data before they start.

This couldn’t be more true for fast-growing businesses like Fibiz.

Fibiz develops a smart platform for fun trading. Their cool marketing campaigns were very successful in attracting many users that generated masses of user events from day one of their beta launch. But trades at that point were done only with virtual money. Realizing that they could find user insights right from the start, they implemented Cooladata’s full stack behavioral analytics and started analyzing their user behavior before their next stage of high growth.

Their goal from the very beginning was to optimize their product for their real money launch. They knew exactly what they were going to do with all of this data.

Understanding the Conversion Funnel Right from the Start

“Being able to get fast insights early on the beta launch, enabled us to implement changes that ensured a better experience to our users. This gave us a serious edge in a fiercely competitive industry,”  said Shahar Nachmias, VP Product at Fibiz.

With behavioral conversion funnel analysis, Fibiz learned that traders responded well to having the tools and ability to understand trading before they started trading. Confident traders ended up placing more trades.

The first behavioral analysis compared new users who completed two different funnels. The first group, after installing the trading platform on their phone, started to familiarize themselves with trading by completing the tutorial before beginning to trade. The second group skipped the tutorial and immediately started trading.

Advanced Conversion funnel on event data

After setting up these two funnels that examine the conversion from App install to the first trade action, Fibiz found that users who completed the tutorial had a much higher conversion rate than users who skipped the tutorial. As a result of this quick insight, Fibiz optimized the app to better engage new users with the tutorial, leading to higher overall conversion.

The organization’s early adoption of analytics benefited both the marketing team and the product team, helping them to both optimize the campaigns for greater ROI and the product for better conversion. Fibiz was able to analyze their campaigns right from day one. The ability to import data from both Facebook Ads and Google AdWords into one main analytics report, for example, helped them understand the different user paths and make data-driven decisions for each the different campaigns. Analyzing the conversion funnel, from the number of clicks on the ads all the way through to the first real money trade helped Fibiz understand that users who made more attempts to trade with virtual money were more likely to succeed in trading real money. Users in certain countries demonstrated this behavior more than other users, and Fibiz allocated their advertising budget in response.

Two in One – Optional Funnel Steps in One Funnel

Why analyze two different funnels separately when you can just do in one? Fibiz engaged the flexibility of our funnel analysis to get insights on two different user journeys with the same point of origin — the app’s installation. They were also able to segment the users of the funnel according to their countries of origin for further insight.

Here’s how.

Funnel 1 (yellow), tracked the users who continued from installation to placing a position (playing with virtual money). Funnel 2 analyzed the path of users who deposited immediately after installation.

Two conversion funnels in oneBy merging the two funnels into one, Fibiz was able to see which paths were most successful per country.

A day’s analysis of trades revealed that users from Tuvalu were the ones who mostly continued to make real deposits that ended up being approved (successful deposits). Fibiz was then able to act on these insights and shift their priorities in their marketing and advertising campaigns accordingly.

“The best thing about Cooladata is that it gave us the ability to access  granular data so we could really understand our users journeys and react quickly,” said Mr. Nachmias.

Anticipating Your Business Goals Early in the Game

Analytics implementation is most successful when, like Fibiz, you are aware of your goals right from the start. In this case, the goals were to optimize their platform and marketing campaign for their launch with real money.

Don’t wait until your startup is big to start implementing analytics. Understand your user behavior as early as possible to be better prepared for your next high stage of growth.

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