Eurographics Conference on Visualization (EuroVis) 2016K-L. Ma, G. Santucci, and J. J. van Wijk(Guest Editors)

Volume 35 (2016), Number 3

Interactive Treemaps for Visualisation of Call Centre DataSubmission # 135

AbstractThere are over one million employees working at over 5,000 call centres in the United Kingdom alone. Someestimates claim almost four million call centre employees in Europe. In this unique application paper we presentmethods for visualising the vast amount of data generated and collected by call centres. We design the applicationto address the challenges of exploration, analysis and visualisation of complex, time-dependant call centre data,and aim to maximise the utility the software contributes to the business stakeholders in the call centre industry.The utility is implemented by the creation of overview visualisations and by encouraging user interaction with thedata by means of focus and context visualisation as well as interactive filtering in a hierarchical treemap view.This application reveals new insight into call centre events that traditional forms of analysis would not as quickly,nor as easily. We also report the positive reaction of domain experts to our visualisations.

1. Introduction & Motivation

Over the past two decades, a rapid expansion has taken placein the call centre industry. With an estimated 5000 call cen-tres, one million employees [Cal], and a revenue of £2.3 bil-lion [rev] in the UK alone, the call centre industry makesa notable contribution to the UK GDP [GDP]. Some esti-mates claim that almost 4 million people are employed ac-cross 35,000 call centres in Europe [eur]. †

Due to the growth of this large industry, it is argued thatcall centres are becoming the modern world equivalent ofthe factory, generating a valuable service as opposed to aproduct [Hud12]. [VvWVdL06]

Focus is often placed on the quality of the service pro-vided by the call centres. It has been noted that there areintangible aspects of customer service that cannot be mea-sured easily or the current measures in place do not accountfor [Gil01]. For example, agents working in a call centre aregiven a temporal target in which they should aim to deal witheach customer. These targets can create a negative impact onthe customer experience and therefore need to be quicklydiscovered and addressed.

The drive for improvement relies on the correct measuresof efficiency and then the ability to present the call centreactivity in an accessible format so that the correct course ofaction can be taken [CM97]. The collection of the call centreevent level data itself is handled by our parter company QPCLtd, however the analysis, exploration, and presentation ofthat data is at an early stage of research. Here we presentmethods for visualising the large amounts of data from a call

† That is roughly 1.3 times the population of Wales [Wal]

centre in a unique application, with the intended end userbeing a decision making manager within the contact centre.

This paper contributes methods by which we can viewlarge amounts of call centre data, hundreds of thousands ofcalls, identifying temporal trends and highlighting issues incustomer wait times. We also explore the important aspect ofcustomers abandoning calls. In addition, the application en-ables a visual exploration of the data through an interactivefocus + context hierarchical treemap that ranges from a fullday overview to a single call detail level. Our contributionsare:

• The introduction of call centre visualisation to the visual-isation community.

• An enhanced focus and context treemap visualisation in afeature-rich application with customised, interactive eventfiltering options.

• Novel interactive filtering options coupled with the focus+ context visualisation that enables users to focus in onspecial subsets of calls of interest.

• Domain expert feedback of the visualisation.

The next section covers the related work followed by adescription of the data we are working with. Then we pro-vide an overview of the software, and describe the features itoffers. Section 5 contains the domain expert feedback fromour industry parters Qpc Ltd with whom we worked to de-sign the software. We conclude by summarising the workand discussing future work in section 6.

2. Related Work

Related work falls into two categories: research related tocall centres and treemap visualisations.

submitted to Eurographics Conference on Visualization (EuroVis) (2016)

2 Submission # 135 / Interactive Treemaps for Visualisation of Call Centre Data

Call Centre Analysis From a technical perspective, theoperation of efficient data routing in a call centre hasbeen researched in the network domain by Adetunji et al.[ASLM07, AL08a, AL08b]. A general architecture of an IP-based call centre was made by Smith in 2007, outliningthe general technical functionality of a call centre [Smi07].These papers focus on the technical design and operations ofthe centre, not the efficiency of their staff, nor the customerexperience.

A call centre’s customer service quality is highly impor-tant to the business it represents because the centre existsfor the benefit of the customer. In many cases it will be theonly point of contact the customer has with the businessand they therefore need to make a positive impact. Raja etal. conducted research in this area to discover what effectsthe employees emotional intelligence, job satisfaction, andwork load have on the quality of the customer service theyprovided [RME∗10]. The cross culture impact on customerservice is also researched between Filipino call centres andAustralian customers [Owe08].

Customer feedback is highly valued within the call cen-tre industry but is costly to obtain. Research into sentimentanalysis aims to allow call centres to calculate the customersexperience without having to collect feedback from the cus-tomer [PGP∗15, GKK∗13].

Treemap Visualisation The original treemap was devel-oped as a space filling visualisation of hierarchical data in1991 [JS91, Shn92]. The treemap was improved by Brulset al. by creating an algorithm that generates more squarenodes [BHVW00]. This enables the user to view better com-pare the nodes against each other. The layout of these nodeswas originally optimised for position, but Shneiderman andWattenberg developed an algorthm to create a treemap thatmaintains an order to the nodes [SW01]. This opens up thevisualisation to be used on hierarchical, temporally-ordereddata.

Treemap visualisation aesthetics have been developed sothat the structure of the tree can be shown through its shading[VWVdW99].

Focus + context visualisation has been applied to thetreemap that preserves the treemap properties, but focuseson selected nodes by enlarging them whilst maintaining or-der [TS08]. The emphasis of the research by Tu et al. is onthe layout algorithm itself and how to efficiently enlarge thefocus [TS08]. User evaluations of treemap browsing havebeen made, analysing the focus + context fish eye and fullzoom views [SZG∗96, SIL05]. Changes in hierarchical datacan be visualised using a treemap as long as it uses a consis-tent visual pattern layout [TS07].

We also present a focus + context treemap. However theemphasis here is on the interactive filtering of the data toenable special event-based questions to be answered.

Huang et al. combined the treemap with a bar chart to cre-ate a hybrid visualisation that can display hierarchical datain a histogram view [HHZ09]. Zhao and Lu created a varia-tion of the treemap that sacrifices the traditional space fillingaspect and replaces it with circular nodes. The benefits ofwhich encourage user interaction through focus + contextfeatures [ZL15].

As a further development of the treemap, Vliegen et al.present business data using various adaptations of a treemap[VvWVdL06]. Some radial methods were used and sometreemap nodes were forces into triangles or leaf shapes.These visualisations are aesthetically appealing but oftensacrifice readability or consistency.

Our work is the first to develop visualisation of call cen-tre data using treemaps. We enhance the traditional treemapvisualisation with customised filtering options especially forthe detection of patterns and outliers in call centre intra-dayevents.

3. Data

Our partner company QPC Ltd provides us with 24 hoursworth of call centre activity data. Each call record containstimestamps for each sub-event, flags to denote the classifica-tion of call and a range of additional information about thecall and customer journey. The data is anonymised to avoidthe release of sensitive data.

Call Components Calls can be broken down into three ma-jor event components.

The IVR (Interactive Voice Response) is the call distribu-tion system that routes the call to an agent with the appropri-ate skillset. The caller listens to pre-recorded messages in-structing them to respond to key-presses corresponding withthe different departments of a call centre. Numerous IVRevents occur per call, which is captured as meta-data associ-ated with the customer journey.

Queue events are instances of the caller waiting in aqueue, usually for an agent. Agent events are instances ofthe caller being put through to a live call centre employee.

There can be multiple queue events and agent events perphone call. All events are given a time stamp and multiplevalues that represent the nature of each event.

Contained within the dataset are other meta-data about thecall; an abandoned flag shows whether the call was hung upbefore the caller got to speak to an agent, the type of call isrecorded (i.e. internal or external call), and details about thedifferent call events.

Challenges: The biggest challenge when attempting topresent data of this nature is one of scale. At over a quar-ter of a million calls, and over five million call events beingcollected each day, the data is difficult to manage. Account-ing for each event collected by the call centre very quickly

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Submission # 135 / Interactive Treemaps for Visualisation of Call Centre Data 3

generates large amounts of data, and attempts at visualisa-tion often result in obfuscation. To overcome this problemprogrammatically, an object is created to represent a singlecall instance, clustering together the events of a call into asingle object. Within this call object all important character-istics are stored, from timestamps to event details, omittingunnecessary details.

4. Interactive Focus + Context Treemap

We created a visual analytics system to explore the call cen-tre data and to identify previously unseen trends using atreemap visualisation. This software utilises the temporal na-ture of the data. Each event contains a time stamp that makesup the building blocks of a call. These events are used tobuild a better understanding of what happens during the call,as well as placing the call on a timeline throughout the day.

Twenty-Four Hours in a Call Centre A novel feature ofthis software is the use of temporal structuring in a treemap.Twenty four individual treemaps, each representing an hourin the call centre show a full day’s worth of events. This isdone by taking advantage of the hierarchical nature of time(i.e. Day -> Hour -> Minute) and splitting the treemap ac-cordingly (See figure 2).

Figure 1: A full hour of calls in the treemap visualisa-tion. The hour is split into six, ten-minute nodes, and theneach ten-minute node is split again into minute nodes. Eachminute node contains the leaf node calls that entered the callcentre within that time. The size and colour represent thelength of each call. Each layer of the hierarchy also main-tains order. Calls appear in the minute node in the same or-der they took place in the call centre.

The 24, hour-treemaps are places in a 4 x 6 grid and varyin size depending on the call volume during that hour (Seefigure 2). Starting and ending at midnight, left-to-right, top-to-bottom.

Interactive Pan & Zoom The twenty four hour gridinitially shows four hierarchical layers (Day->Hour->TenMinutes->Minute), where the colour of each minutenode represents the percentage of callers who abandon the

call. We observe the increase in abandoned calls from 7-9pm in figure 2. We hypothesise that the call centre is un-der staffed during those hours which results in a reductionof service quality. A user option enables the fifth hierarchi-cal layer, the individual call layer. Users can click and dragto pan over the data as well as zoom in to take a closer lookat the individual calls and events. This allows the user to ex-plore the data initially as an overview and seamlessly transi-tion into a detail view.

Figure 2: This figure shows the 24 hour overview where allcentre activity is displayed. Starting and ending at midnight,left-to-right, top-to-bottom. A larger call volume within anhour node, results in an increased size. Minute node coloursare mapped according to the percentage of people whoabandoned the call before talking to an agent.

Interactive Detail Level Mouse-Over When the fifth hier-archical layer of detail is active, the user can view individ-ual calls (See figure 3(a)). This feature enables the user tohover the mouse over a call instance for an information boxto appear. This further details the call with a event treemapshowing the proportion of time spent at each call stage, andtiming information about the call,.Interactive Focus & Context Filtering A main feature ofthe software is filtering of the data in order to answer specialdomain expert questions. The overview allows the user to seeall records of calls, but some patterns in the data might notbe immediately visible. Filtering the data by parameters suchas event lengths, or call type flags enables further insight.

Figure 3 shows a comparison of an hour node at 13:00with different filtering options enabled. Sub-figure a) filtersout all outbound calls leaving only inbound calls. No ob-vious pattern is revealed in the call behaviour. Sub-figureb) only shows callers that spend longer than five minutesqueuing. We observe that there are significantly more callswaiting longer than five minutes between 13:00 and 13:15.This suggests that the centre might need to stagger sched-uled lunch breaks for the staff. Sub-figure c) displays allcalls where the caller spoke to an agent for longer than 50minutes. The lack of long calls during the busy first fifteenminutes suggests that the quality of service decreases whenthe call centre is under heavy load. Agents are more likely toend calls early to prevent queues building further. please seethe accompanying video for more details.

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4 Submission # 135 / Interactive Treemaps for Visualisation of Call Centre Data

Figure 3: These images shows the versatile focus + context filtering feature. a) shows a filtered view containing only inboundcalls into the call centre with the addition of a call hover over display window that further details the call. b) shows all callerswho wait longer than 5 minutes to talk to an agent. c) shows all calls where a the caller talks to an agent for more than 50minutes. d) shows all calls that were abandoned.

5. Domain Expert Feedback

The call centre industry lags behind the other advanced data-driven industries such as Chemical and Nuclear power. Thisis a direct result of the perception of the call centre indus-try being a low paid, low skilled ‘factory’. The industry isexpected to undergo the same advancement production linefactories have experienced over the last 10 years to intro-duce high levels of automation, quality control, & cost con-trol drivers that revolutionised the global industry. Call cen-tres are central to the delivery of an integrated omni-channelcustomer experience and as such central to driving increasedcustomer loyalty.

This research project is designed to bridge the percep-tion and skill gap in the call centre industry by creating ad-vanced visualisations of the unique data collected by QPCLtd by demonstrating previously hidden and unmanaged op-erational insight. The hierarchical treemap visualisation pro-vides an intra-day perspective of performance. This visu-alisation has provided us with a never-before-seen insightinto the data, highlighting to us the importance of balancedstaffing levels throughout the day.

Visualising the intra-day data in the treemap is a new con-cept in the call centre industry for visualising data. This ap-plication to intra-day data has not been previously attemptedand this marks its very first use. The treemap visualisationwill speed up the ability for the end-user to spot patterns and

trends. The end user in their operational role, still requiresaccess to a tabular format of this data, to quantify any im-pacts and action accordingly, they can use the treemap visu-alisation as a means to react to significant trends.

This tool helps end users in the exploration phase of anal-ysis, the ability to surface significant trends and the associ-ated impact in an intuitive way, is key to the success of theapplication. Adding outcome data and using the treemap vi-sualisation to filter and segment, provides more context andimpact when used in an operational capacity.

6. Conclusions & Further Work

We present a novel way of presenting temporal event-basedcall centre data using a hierarchical treemap visualisation.The visualisation has identified previously unseen trends inthe call centre by means of a focus + context filtering sys-tem for visual exploration and analysis. Domain experts haveprovided feedback stating the utility of this system as well asthe valuable insights it produces.

This is a work-in-progress project. We are continuing theresearch by investigating new ways of visualising the callcentre environment, and producing visual analytic systemswith an intended end user of the call centre industry. In thefuture we hope to examine the visualisation potential of cus-tomer feedback/loyalty data.

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Submission # 135 / Interactive Treemaps for Visualisation of Call Centre Data 5

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