May 29, 2017
Everyone already knows it: all our online actions are being recorded, whether it’s the first click on an ad, multiple visits to a website, the first registration in the foreign exchange trading platform, a first-time deposit, or pressing the play button on a tutorial. Each and every action traders take is part of the complete story of a trader’s digital behavior, or as marketers call it – the customer journey.
As McKinsey explains, focusing on these single touchpoints misses the bigger picture: the customer’s end-to-end experience. Only by viewing the customer experience through your customers’ eyes can you finally start to understand how to improve performance.
Compiled by many single actions arranged on a timeline, the trader journey is often complex to comprehend. But, as with many things in life, it’s about asking the right questions. With the right questions in hand and the right tools to analyze online behavior, brokerages can receive the correct interpretation of the trader story, which leads to valuable insights and actions that eventually contribute to higher conversions and continued trading.
Most brokerages rely on simple KPIs such as the number of sessions and registrations, the total of deposits, the rate of FTDs (First Time Deposit), or the number of demo trades. But these don’t give businesses a true understanding of their performance or the complete data story of their traders. In order to gain an edge in this fiercely competitive industry, brokerages need to be able to quickly answer vital business questions such as:
To answer such critical business questions, all trader actions data from across the different data points is collected and joined together. The raw event data of user actions are the building blocks to a deep understanding of trader behavior.
Trader journeys are often complex, relying on data from multiple touchpoints which come from a variety of the web or mobile apps, affiliate data, trader data from a brokerage’s CRM or Affiliate data. Data might originate from the ad clicked before coming through to the registration page, or from the first trading steps all the way to the CRM. Moreover, each data or session might be attached to a separate user identity. To analyze the trader journey as a whole, those different datasets must be joined under a single unified user identity.
Based on these capabilities, behavioral analysis of the data can shed great insight on the complex trader journeys to conversion and retention, allowing brokerages to react in real-time to maximize trader engagement.
Here are a few examples of how brokerages do this:
Advanced analytics can help identify the valuable traders based on their actions and build trader segments, such as whales (those traders who have a high likelihood of higher retention and higher deposits).
Source: Cooladata Trading Analytics
On the other hand, brokerages can identify the typical behavior of those about to churn, the one-time traders.
These are the types of insights a platform can only glean over time, by gathering raw data collected from massive traffic which is then analyzed using funnel analysis, path analysis, and cohort analysis to compare behaviors and find patterns that are revealed when observing actions over time. And by identifying these trader profiles in real-time, businesses can focus on optimizing the profiles most likely to maximize their ROI.
It is then possible to integrate this information with data from marketing campaigns as well as financial data about chargebacks to gain a more accurate understanding of these trader profiles. If traders who are considered whales have high chargeback amounts in a trading platform, then they are costly, and should not be considered a source of top revenue for the business. But the only way to know whether or not these traders are valuable is by joining raw data from these different platforms to gain a better understanding of the complete trader journey.
Once brokerages understand which traders are valuable, advanced analytics can show the top marketing channels or trading assets for that trading platform. Brokerages can use this more accurate understanding about trader behavior to adjust their marketing campaigns to focus on the most successful trading assets, channels or affiliates. The ability to understand which trading asset is most popular for each trader is especially valuable for foreign exchange brokerages.
Source: Cooladata Trading analytics
Not all traders make it to deposits, which is why being able to identify traders most likely to make a deposit is extremely valuable to brokerages. Brokerages should focus their efforts to optimize the numbers and amounts of these FTDs.
This combined line and bar graph, below, joins and integrates marketing and payment data over the entire month of March using advanced analytics to display the number of leads (green) in contrast to the rate of deposits (blue). We can see that in the middle of March, there were over 1,000 leads but a less than 1.25% deposit rate. Later in the month, however, lead generation became more targeted, with only a few hundred leads but a conversion rate of over 5%.
Source: Cooladata Analytics
Drilling down further can reveal even greater insights. By querying the number of traders that joined per day over a four-day period and how many days they waited to make a first-time deposit, brokerages can have a better understanding of which marketing campaigns were more successful in driving FTDs.
Source: Cooladata Trading Analytics
Forex is one of the most competitive and expensive industries to compete in. One of the best ways of gaining an edge over your competition is by having a better understanding of your trader behavior. Advanced analytics – which collects, analyzes, and integrates data from multiple platforms, touchpoints, devices, and sessions – offers this advantage. This ability to receive a more holistic view of the trader journey, and the ability of brokerages to react in real-time to these insights, is what will drive the future of online trading.