🌐 Challenge: Launch more effective paid acquisition campaigns by identifying trending instruments across competitor brokers, segmented by trader experience — to improve targeting, messaging, and conquest efficiency.
👀 Task: Use real-time trading behaviour — segmented by experience, lot size, and instrument — to uncover what beginner and experienced traders are doing, and how recently, to inform targeting and content development.
🎯 Problem
The acquisition team lacked clarity on what inexperienced traders were doing across the market. Without segment-level behavioural visibility, their campaigns relied on generic messaging, leading to wasted CAC and inconsistent conversions.
🧠 Solution
TFE’s behavioural intelligence layer helped the platform:
- Identify which instruments were trending by experience level
- Detect high-risk segments based on lot size behaviour (e.g. aggressive exposure among new traders)
- Segment users into actionable clusters for targeting (e.g. Overexposed Rookies, Trend Followers, Selective Veterans)
- Deploy targeted messaging and creative aligned to real-time trading behaviour
💡Key Results
📉−28% reduction in cost-per-funded-account
after launching behaviour-based campaign targeting
🎯+12% increase in funded accounts
from overexposed, trend-driven traders previously underperforming in generic campaigns
🧲+41% lift in CTR
on creative aligned to specific instruments (e.g. gold, EUR/USD, oil)
📈3-week campaign sprint
informed by real-time TFE segmentation and instrument trends
🔍 Initial Assumptions
The team hypothesised that:
- Traders with high lot sizes in volatile instruments (e.g. oil, USD/CAD, XAU/USD) were either overexposed or trend-following
- Newer traders were more likely to be swayed by market narratives, and thus needed messaging that addressed risk and control
- Experienced traders would respond to more precise or directional content (sentiment alignment, timing windows, etc.)
📊 Data Required
In order to calculate and validate high-value switchers, we use the following data signals:
Area to Assess | Rationale | Combination Variables |
Experience Level | Strategy quality and trade durability differ by tier | All for Low experience level |
Instrument Popularity | Identifies content themes & trending narratives | Instrument + experience tier |
Lot Size Patterns | Indicates risk appetite and intent | Lot size + experience tier |
Trade Recency | Content/campaign needs must follow real-time behaviour | Time of last trade + instrument volume |
Broker Movement | Targets conquesting based on quality flows | From-broker + instrument overlap |
Data Transparency Note
This case study uses partial, illustrative data extracted from the TFE platform to demonstrate how experience-level and instrument-based trading behaviour can be used to drive strategy.
We’ve intentionally omitted all provider-identifiable intelligence and broker-level signals in this public-facing version. Full access is available via the live TFE platform at TFE.ai.
🧪 How They Did It
The growth team used TFE’s API to:
- Pull real-time instrument usage data segmented by experience level
- Calculate average lot size per asset, exposing speculative patterns in key instruments
- Cluster user types based on directional bias (buy vs sell), lot size, and instrument overlap
- Feed these segments into a multi-touch campaign across PPC, paid social, and CRM
Experience Level Across Instruments & Lot Size
🔹Insight: Average Lot Size By Experience Level
🧠 Insights:
- Traders with 3–4 years of experience had the highest average lot size (20.56), suggesting growing confidence or risk tolerance.
- In contrast, newer traders (1–2 years) showed a moderate average (6.46), while the 5+ years group had the smallest lot sizes (2.96) — potentially signalling tighter risk control.
- The trend suggests that while intermediate traders increase position size, the most experienced may trade more selectively or hedge risk more precisely.
🔹 Insight 2: Recent Instrument Choice by Low Experience Level
🧠 Insights:
- XAU/USD (Gold) and EUR/USD dominate with 38.16% and 35.75% of trades respectively among inexperienced traders — indicating risk appetite skewed toward volatility and familiarity.
- Crypto (BTC/USD) and exotic FX pairs (e.g. GBP/JPY, USD/JPY) also appear, reinforcing a possible pattern of speculative overconfidence in low-experience cohorts.
- These choices offer key opportunities for content targeting (e.g., gold volatility explainers, EUR/USD trade timing guides) and campaign conquesting.
Instrument Choice by Lot Size & Direction
🔹 Insight 2: Instrument Choice by Direction
🧠 Insights:
- Buy orders dominated among low-experience traders (63% vs. 37%), indicating trend-following or FOMO-based trading behaviour.
- Educational content that frames when not to buy or highlights profit-taking strategies could improve engagement and conversion.
🔹 Insight 2: Average Lot Sizes for instrument Choice
🧠 Insights:
- The largest lot sizes were concentrated in:
- USD/CAD (13.69)
- GBP/USD (13.25)
- OIL (13.25)
- These patterns suggest aggressive exposure in macro-driven instruments among less experienced users.
- Conquesting content should prioritise volatility management and instrument-specific risk framing.
🔎 What They Saw
- XAU/USD and EUR/USD dominated novice trader volume
- Highest lot sizes came from USD/CAD, GBP/USD, and oil — instruments with macro/trend sensitivity
- Buy bias (63%) signalled FOMO-driven positioning in early-stage traders
- Veterans traded less frequently, with lower exposure and higher timing precision
⚡ Comparative Overview: Segment Breakdown
Segment Name | Avg Lot Size | Risk Score | Instrument Bias | Notes |
Overexposed Rookies | 13.2 | High | Oil, USD/CAD, GBP/USD | Aggressive lot sizing, low control |
Trend Followers | 6.4 | Medium | Gold, EUR/USD | Volume-led, pattern dependent |
Selective Vetrans | 2.9 | Low | GBP/USD, EUR/USD | Small size, high-timing precision |
👀 Final Signal: Competitive Instrument Movement
While we’ve removed broker-specific data, the directional trade activity, lot size concentration, and instrument trends point to clearly shifting trader intent. This insight layer can:
- Inform instrument-led conquest campaigns
- Support better risk-adjusted messaging
- Reveal real-time volatility opportunities
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🔎 What They Saw
- XAU/USD and EUR/USD dominated novice trader volume
- Highest lot sizes came from USD/CAD, GBP/USD, and oil — instruments with macro/trend sensitivity
- Buy bias (63%) signalled FOMO-driven positioning in early-stage traders
- Veterans traded less frequently, with lower exposure and higher timing precision
✅ Outcome
To solve this challenge, the client used TFE’s API to:
- Pinpoint which instruments were trending among inexperienced traders
- Map lot size patterns and behavioural signals by experience tier
- Identify buy/sell sentiment shifts to inform timing and creative messaging
By identifying which instruments were trending among newer traders — and segmenting by experience and lot size — they:
- Built real-time content campaigns around instruments like gold, EUR/USD, and oil
- Launched PPC and retargeting ads aimed at traders displaying speculative behaviour on volatile pairs
- Created messaging variants tailored to novice vs. experienced user segments, highlighting education, control, and volatility opportunities
This enabled them to attract a wider group of traders with specific behavioural intent, reduce blanket targeting, and increase both funded account rates and engagement depth.
📉 Result:
They improved campaign relevance, cut wasted CAC, and increased first-time funded accounts from key segments by double digits.
📦 Get Full Access
With full access to TFE, you get:
- Real-time trader flow data segmented by instrument, experience tier, and lot size
- Access to the Trader Conquest Index — showing which assets and segments are heating up
- Directional trade bias data (buy vs. sell) across asset classes
- Lot size heatmaps to identify overexposure or risk clusters
- API and dashboard access for your growth, content, and product teams
- Embedded chart and signal modules to support campaign planning or content strategy
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