Author: Patrick Jordan for Gain Capital, May 2016

Proposed segments

Our hypothesis is that we should segment using a single primary variable – trading behavior and knowledge

  Segment Style Description


No system

Underestimate how difficult trading is

Often trade on a news headline, event or gut instinct

Likely to lose their money quickly and not return

Large group (approx. 50-60%), low value per user


System but lack discipline

May have a system, but don’t stick to it consistently

Lack discipline and let their emotions get the better of them

Show no improvement with experience

Large group (approx. 30-40%), low value per user


System with discipline

Develop and stick to prudent strategies

Disciplined and manage their emotions

Learn and improve as they trade

Small (<10%), high value group per user



Earn a high proportion of their income from trading

Many have a professional background in trading or finance

Spend hours per day trading

Very small numbers (< 1%), but very high value per user



Not interested in learning to trade but want to make money from it

Risk adverse

Hands off – all about reporting and tracking

Gender balanced

Very large group, potentially high value

Trading patterns

Analysis of individual trading data revealed patterns that were characteristic of each segment (based on qualitative analysis of data from 50 clients)

Segment Characteristic trading patterns


A flurry of large (compared to account size) early losses can wipe out account

May do some small trades, build confidence and then overleverage leading to wipeout

If have sufficient funds may be able to keep going longer-term but likely to lose heavily


On average have a higher percentage of wins than Diligent traders

Run losses, cut profits

Settle quickly into a pattern of trading

Maintain this pattern over a long period of time even though it isn’t working

Focused on each individual trade rather than the big picture

Can have ‘escalating meltdowns’ where a big loss is followed by several more as panic and revenge trading set in

Often these prove catastrophic

A run of successful disciplined trading can lead to overconfidence and reliance on their ‘trading instincts’ (punting) with catastrophic consequences


On average have lower percentage of winning trades that Aspiring traders (probably because they are being more disciplined with stops and limits)

Cut losses, run profits

Focused on the big picture rather than every individual trade (this is known as having a probabilistic midset)

Trading patterns change over time as they improve

May still have ‘meltdowns’ but step away before they become catastrophic

Generally maintain discipline and recover it quickly if lost


Wider variety of successful patterns than Diligent

Mostly based on having bigger wins than losses

Some succeed through having more wins than losses even though losses bigger

Combine discipline with better win/loss ratio than Diligent


Win/loss ratio is a poor predictor of PnL, which is usually more dependent on size of average win/loss

Codifying these trading patterns in analytics is the key to validating the segmentation

Mapping segments to value

Currently clients only generate value for us after a certain amount of trades


To maximize value and to meet user needs we should help clients to move into the high value segments

Create separate offers to match the needs of our users and accept that some of those users will not progress to be diligent or expert

Key user experiences

Our segmentation hypothesis suggests that we should design three types of user experience, in order to meet users’ needs

User experiences

UX 1: Trade quick

Easy to place trade

Don’t need to understand trading

(Mental models from investing/gaming)

Gateway to UX2

UX 2: Trade and learn

Facilitate Trading

Facilitate Learning

Journey to Diligence

Gateway to UX3

UX 3: Trade optimally

Better decision making

Stretching ambition

More professional feel



Money Square

CI Campaign Mar'16

Next steps

What we need to do next and why

Activity Why? How?


To check if there really are four segments that differ according to trading behavior and knowledge

Adjust segmentation model if necessary

Analyze trading data to see if patterns appear that are consistent with the behaviors associated with each segment

Quantify these


Enrich the segments by finding out more about the people in each

As well as varying according to the primary variable are there differences in trading styles and ambition, psychographics etc.

Issue questionnaires to gather psychographic and trading information about users

Use Google Analytics to understand users’ trading styles

Map both of these onto the segments


To embody the users in each segment in ‘people’ we can design for

To highlights the different kinds of people within each segment, for example in terms of trading styles and ambition, psychographics without creating separate segments for each

Share the enriched segmentation with key stakeholders

Hold workshops to create personas

Analyze the design needs associated with each persona to inform UX solutions




Jack Robbins (24)


Business Studies student, UCL


Finds idea of trading glamorous

Wants to make quick money

Trades on big news

Trading for a month

Needs cluster Explanation
Consideration setRobinhood; eToro; Plus 500; Avatrade; SpreadEx
ContextIndividual shares; forex
InfluencersFacebook; BBC; Buzz feed; Yahoo Finance, Guardian, Forbes, BBC
GoalsMake a lot of money quickly
Purchase criteriaEase of onboarding; usability
Beliefs/ValuesTrust your instincts and act decisively
Trading habitsOpportunistic; trades long or short based on headline news, friends’ recommendations
Basis of decisionNews headline and gut instinct
Performancepattern Has 50:50 win rate but runs losses and cuts gains; over-leverages; no stops on earliest trades
Trading timesEvening and intermittently throughout day
PlatformsWeb and smartphone; uses both to place and monitor
Subject knowledgeBased on ‘Wolf of Wall Street’ image
Path throughSearch — Place Trade — Monitor
Secondary benefitsWolf of Wall Street’ image

Jack has heard about trading and thinks that it offers the opportunity to get rich quick, but he has no real understanding of how it works.

He has put £200 in his account and has almost blown it through over-leveraging (he doesn’t properly understand the concept) and running losses.

He almost blew his account in one trade due to not putting a stop loss in place. He won’t last much longer.

Jack has heard about trading and thinks that it offers the opportunity to get rich quick, but he has no real understanding of how it works.

He has put £200 in his account and has almost blown it through over-leveraging (he doesn’t properly understand the concept) and running losses. He almost blew his account in one trade due to not putting a stop loss in place. He won’t last much longer.



John Marsh (37)

Barnet, London

Estate agent

Married, no children

Previously invested in shares

Market wasn’t doing much so turned to trading

Trading for a year

Needs cluster Explanation
Consideration setIG; CMC; Plus 500
ContextTrades indices; shares
InfluencersBBC Business App; Money Week; Reuters; Bloomberg;
GoalsMake a lot of money quickly
Purchase criteriaCharting tools; trust; usability
Beliefs/ValuesAny win is good; any loss is bad; thinks his winning record shows he’s a good trader
Trading habitsLooks at each trade individually rather than as part of a sequence
Basis of decisionLargely gut instinct following superficial analysis of news and charts
PerformanceCuts gains and runs losses; more wins than losses; pattern became fixed early
Trading timesEvening and intermittently throughout day
PlatformsWeb and smartphone; uses both to place and monitor
Subject knowledgeDiscusses with friends; goes on trading forums; watches tutorials
Path throughSearch or watchlist — Chart — Place Trade — Monitor
Secondary benefitsImage of being a trader

John is interested in trading as he sees it as a way of making money quickly. He is reasonably knowledgeable but lacks ‘probabilistic thinking’, meaning that he puts too much emphasis on individual trades, leading to cutting gains and running losses.

He has been stuck in this pattern since early on. He has an unrealistically positive view of his ability because he tends to focus on his wins more than his losses, which he often puts down to bad luck.

Has had a couple of occasions when he feels he has been ripped off by previous broker and moved as a result

Like all Aspiring traders, John has become stuck in a pattern of trading that causes him to consistently lose money.

While he only carries out superficial analysis and relies to a large extent on instinct, others in this segment will be more systematic.

However, like John most of them will lack discipline and so still end up losing money.

Diligent (developing)


Peter Clarke (62)


retired electrician

married, children, grandchildren

Wants a quicker return on investment as aging

Shares & bank low returns

Trading for six months

Needs cluster Explanation
Consideration setIG, CMC, City Index, ETX Capital; SpreadEX
ContextTrades indices; commodities
InfluencersBloomberg; BBC; Digital Look; Telegraph
GoalsBetter return than investment; possibly looking to do full time
Purchase criteriaSpreads; allowing small stakes per point; charting tools
Beliefs/ValuesSeeks to find an edge through analysis; not interested in ‘punting’; accepts will have losing trades; disciplined
Trading habitsExperimenting with different systems/analyses; reviewing performance
Basis of decisionMostly chart-based analysis
PerformanceChanging significantly from week to week; gradually improving
Trading times8.00 -9.30 am and 3.00 – 4.00 pm (times of greatest volatility)
PlatformsDesktop application for placing; phone for monitoring and occasionally closing
Subject knowledgeOnline tutorials; learn by doing; investment experience
Path throughWatchlist — Chart — Place Trade — Monitor
Secondary benefitsEnjoys the analysis and the challenge of learning

Peter has recently retired. He enjoys trading and is keen to learn, experimenting until he finds a winning analysis system. He is very chart focussed but also consumes financial media.

While he learns he is putting on small stakes. He is trading at highly volatile times of day which is risky for a beginner, but gives learning opportunities.

Peter mostly trades off charts which is common within this segment. However, there are also Diligent traders who will be more news focussed.

A key characteristic of a developing Diligent trader is that they will try different strategies and approaches, learning and refining them.

Diligent (established)


Rodney Slade (51)

Norbiton, London


Married, 2 children

Invested in stock market

Modest returns, wants more

Sees trading as an option

Has been trading 4 years

Needs cluster Explanation
Consideration setIG, CMC, City Index
ContextTrades forex pairs and various indices (UK, USA, Germany)
InfluencersBloomberg; BBC; Sky News; FT
GoalsBetter return on savings than bank or investments
Purchase criteriaSpreads; customer service; trustworthiness; charting tools; news
Beliefs/ValuesRational; understands that trading takes a lot of time and effort to get right
Trading habitsHighly disciplined; working on optimizing system/plan
Basis of decisionChart-based analytics; also sensitive to news
PerformanceMore losses outweighed by bigger wins; improved over time
Trading times7-8pm in the evening for placing; monitor during day
PlatformsDWeb for placing trades; phone for monitoring
Subject knowledgeLot of investing experience; no trading experience; self-educating online
Path throughWatchlist — Chart — Place Trade — Monitor
Secondary benefitsEnjoys studying trading and making further marginal gains

Rodney works full time and has a busy family life. He manages to find an hour per evening for trading.

He is trading outside UK and Europe market hours, so focusses on live trading forex pairs and places conditional buy/sell orders on indices which are executed the next day provided the criteria are met.

Established Diligent traders have found a way of trading that works for them. Others in this segment may have very different systems to Rodney.

However, like Rodney, they will stick to them in a disciplined manner and learn from their mistakes.



Paul Jackson (67)

Epsom, Surrey

Retired stock broker

Married, 3 adult children

Traded professionally

Retired 10 years ago

Trades for himself since then

Makes significant income

Needs cluster Explanation
Consideration setIG, CMC, City Index
ContextFTSE index
InfluencersBloomberg; Reuters; Financial Times
GoalsEarn a living from trading
Purchase criteriaSpreads; execution speed
Beliefs/ValuesThe key to success is discipline and risk management
Trading habitsVery disciplined at managing risk; if hypothesis wrong gets out right away; if right sees it through
Basis of decisionUses news to find opportunities; charts to decide when to open/close; occasionally relies on instinct
PerformanceWins over half his trades; runs gains, cuts losses; established pattern
Trading timesThroughout the day
PlatformsDesktop application for placing trade; smartphone sometimes for monitoring; third-party charting software and news feed
Subject knowledgeVast professional knowledge and experience
Path throughPlace Trade — Monitor
Secondary benefitsFreedom of being own boss

Paul has vast experience and knowledge of trading. He treats his trading like a profession and is extremely disciplined about when and how he trades.

Has established a system based on a single index and has gained an implicit knowledge of its behaviour patterns enabling him to use instinct effectively from time to time.

Different Experts have different strategies and trade different products. Although Paul only trades the FTSE index, others may trade a wide range of products and use different analysis techniques to him.

His discipline and risk management is something common across the segment.



Cynthia Cooper (33)

Brentwood, Essex

HR Specialist

Married, one child, pregnant

Has investment in FTSE tracker

Sees trading as opportunity for better return

Sees trading as risky & difficult

Needs cluster Explanation
Consideration seteToro; Plus 500; Finspreads
ContextExploring: considering social trading or trading indices or forex herself
InfluencersBBC; Business Week; This is Money; Guardian
GoalsExtra income; better return than bank or stock market
Purchase criteriaEase of use; customer service; ease of opening; news feed
Beliefs/ValuesTrading is very hard and time consuming; wary of doing it
Trading habitsNone yet; considering different approaches
Basis of decisionEither by following others or learning how to do it herself
PerformanceNone yet
Trading timesWould be able to give it a lot of time to start with; much less when back at work
PlatformsThinking of starting on web or desktop app
Subject knowledgeSome investing experience; little trading knowledge; keen to learn
Path throughNone yet
Secondary benefitsInteresting thing to learn while on maternity leave

Cynthia is disappointed at the rate of return that she has been getting on her savings and investments. She is looking at options for getting a better return, one of which is trading.

She is under no illusion about how difficult and time consuming it is making her cautious about getting involved. Nevertheless she is open to exploring it further.

Like many investors who don’t trade Cynthia is wary of the difficulties associated with it and the time required to do it well.

She is more cautious and rational and unlike some other investors, indifferent to the excitement and image that go with trading.

A very small percentage of retail traders are women. She may access different media channels and respond to different messages to her male counterparts in this segment.

Automated trading personas

To adjust these personas for automated trading use the table below

Persona Segment Signals Habits Basis of decision Notes
Jack Robins HopefulSocial; EAPicks signal and appliesLeaderboards; promised returnsHopefuls are likely to be tempted by the ‘get rich quick’ claims associated with particular signals. Will select traders and signals from leaderboards without understanding how they work
John MarshAspiringEA; algorithm; socialSome back-testing of signals where possibleLeaderboards; back-testing resultsMay do rudimentary back- testing without understanding the conditions under which a signal succeeds or fails
Peter ClarkeDiligent (developing)EA; algorithm; socialThrough investigation of signal’s characteristics; forward and back-testing in different markets and market conditionsMatching signal to marketsUnderstands that leaderboards favour high-risk signals. Risk profiles signals and valuates their effectiveness under different circumstances
Rodney SladeDiligent (established)EA; algorithm; socialThrough investigation of signal’s characteristics; forward and back-testing in different markets and market conditionsMatching signal to markets; selecting a signal that matches financial goals and psychological profileAs well as understanding the risk profiles and of signals he has gained experience of what he can and can’t handle psychologically, for example in terms of win/lose ratio, volatility and downdraws
Paul JacksonExpertEA; algorithm; socialMay create his own EAs or algorithmsCodifying his expertise and experience to create signals that give an edge in the marketHe may write his own algorithms or create signals based on indicators. Being a social trading guru may interest him as a source of additional income
Cynthia CooperInvestorConsiders social; EAsWill research the potential of EAs and social trading; may regard algorithms as too complex for nowSearching for a signal that will enable her to trade in a low risk, low effort wayAutomated trading may be a good option for her if it enables her to make a good return without having to spend too much time trading