How Trading Companies are Leveraging Behavioral Analytics to Win Conversions and Retention

In the dynamic trading industry that relies so heavily on trader conversions and retention, traders need to understand what drives customers toward achieving their goals. In order to understand this, traders need to be able to analyze not just digital analytics, but digital behavior over time.

When thinking of analytics, it’s not simply Google Analytics. Google analytics is great for a basic understanding of visitors and customers. How many visitors are on the site now at which pages? What geographic region are they in? What advertisement prompted them to click? But these surface insights do not shed light on behavior. This is what I call static data, a one-dimensional snapshot of one single touch point on the website.

That’s where behavioral analytics shapes a whole new future for trading companies. By leveraging this approach, traders are able to go beyond traditional analytics to understand behavior over time.

Behavioral Analytics in Trading Companies

What started out as a business intelligence tool for eCommerce companies has now expanded to dozens of industries – from online games, to web and mobile applications to IoT and now FinTech. For trading companies specifically, behavioral analytics present a timeline of user actions.

This isn’t just about a single trading action, but a complete picture of the trader’s journey, a series of events over time that brings insights into trader behavior. This alone enables trading companies to analyze retention by user and optimize the customer path to becoming a loyal one and thus boosting retention.

Just a short while ago, being able to analyze a trader’s behavior was not an option. A new dawn is upon us, as with all the data from a trading platform like MetaTrader for example, combined with CRM and financial data, trading companies are able to learn where leads congregate and what the hottest trading trends on the market are.

THIS is the disruption that behavioral analytics brings to the industry.

Connecting the Dots

The trader’s journey to successfully opening a position and making their first deposit is comprised of a few different touchpoints. Take repeat deposits for instance: the most loyal customers pretty much follow similar paths towards that goal. It most probably starts with a click on an ad campaign, perhaps a banner on a popular trading site, then to a short video and an invitation to open a demo account, then to their first real trade.

The trader journey to that first deposit with the company, and to future loyalty to the brand, is comprised of those many different touch points , with user action data created for each of these events.

The ability to understand trader behavior heavily depends on being able to stream and unify the plethora of data from across the different touch points. The marketing campaign data, combined with the web and mobile action data, joined with the MetaTrader trading data and the CRM financial data.

Finally, it is ripe for analysis. Now imagine what traders can do with streams of data from all sources, fully managed in a cloud-based data warehouse, that they don’t need to worry about maintaining or paying extra for. The raw data is just there, waiting for a query asking the most complex business questions and to get immediate answers.

Unified Data in Action

How are new users getting from registration to FTD? Who are the top 10 affiliates? Which campaigns brought the most First Time Depositors? Let’s take an example from Fibiz, a smart trading app business, who implemented behavioral analytics and used the power of unified data with advanced conversion funnel analysis.

Fibiz compared the same conversion funnel from app install to opening a trading position, between users who watched the tutorial videos, and the ones who skipped it. That comparison, gave them the insight that traders who watched the video, continued to the conversion step at a much higher rate of opening a trading position.

Source: The Cool Behavioral Analytics Blog

This is what unifying data is all about, being able to analyze the conversion funnel right from the app install (provided by Appsflyer mobile attribution) together with actions done on the mobile app, provided those valuable insights.

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 “Shahar Nachmias “ VP Product at Fibiz

Retention “ What is the retention rate and who are my most loyal customers?

Retaining customers is just, as if not more, challenging than generating leads. A trader might as well nurture the known (current customers), rather than trying to bring in the unknown.

Utilizing retention cohort analysis, traders are empowered to see all clients from when they registered to how often they came back to perform an action or a set of actions over a period of how many days you specify. Trading companies are able to drill down into the cohort to find groups of users to target.

Utilizing behavioral segmentation, they can put a targeted group of users into their own segment and hone in on them with any campaigns you’d like in a timely and efficient manner, whether it be an email, push notification or Facebook ad campaign.

Source: Cooladata Trading analytics

Deep Analytics Serving Risk Management

Assessing risk is a major aspect of operating a Forex brokerage. One must be able to see data in real-time along with getting alerts based on specific preferences, market statuses, P&L, Symbol exposure and volatility of the market. Performance managers can obtain a top-down view on platform performance giving them immediate awareness. The key to obtaining such a view is the unified data emanating from the entire spectrum of resources (Web, mobile, social, CRM, affiliates, etc.)

Risk Managers can then drill down further to get a granular view of risk by user. What’s more, sharing this data in a highly secure manner is paramount, so that all stakeholders are involved and engaged in quick and efficient decision making.

This way of analyzing trading data has already been implemented at some industry leading companies with great success.

Source: Cooladata Trading analytics

Remember, every trader action or series of trader actions whether it may be on mobile, web or social when integrated with CRM and financial data is a paragraph in a story waiting to be told. Behavioral Analytics is your tool to uncover those stories and grow your business.

To learn how to harness the power of advanced analytics to optimize the trader’s’ journey, increase conversions, maximize marketing ROI, boost retention and increase FTD rate, download Cooladata’s essential guide to trading analytics.