The retailers guide to data discovery - EM360 · 5 The retailers guide to data discovery // Whitepaper Retailers need to stay ahead of consumer demands and insight is critical for

The retailers guide to data discovery

How smart retailers are using visual data discovery to search for actionable insights that boost profits and help them understand their customers next move – quicker than the competition.

The retailers guide to data discovery // Whitepaper2

Table of Contents

Introduction 3

The search for customers, products and profit 3

Swamped by data but still seeking insight? 4

Harnessing big data 4

Overcoming data silos 5

Eradicating the time warp 5

Visual Data Discovery: more than a pretty face for retail intelligence 6

The freedom to search and explore 6

Accelerating discoveries through cool, clear visuals 7

Increasing efficiency and enhancing ROI 8

Applications of visual data discovery tools in retail environments 9

Store Operations 9

Sales Channel Analysis 9

Customer Behaviour Analysis 10

Merchandise Management 10

Supply chain analytics 11

NeutrinoBI – visual data discovery powered by freeform search 12


Introduction

In the fast paced, rapidly changing and highly competitive retail sector, today’s

smart retailers rely on business insight in order to attract customers and operate

more efficiently to increase revenue and profitability. Data is the heart-beat of this

insight – but extracting the most valuable data from multiple sources and turning

it into actionable information is a major challenge. Getting answers to today’s

burning questions and informing the right person in time to help them make the

right decisions has, until now, been almost impossible.

To overcome this challenge, retailers are increasingly turning to Visual Data Discovery tools as a key

component of their toolkit. Complementing existing BI solutions, these self-service BI tools enable line of

business decision makers in both store-front and headquarters to explore, discover and share real-

time insight. In this paper we will explain the benefits that data discovery can bring to a range of retail

applications. We will also introduce you to NeutrinoBI - a new generation of visual data discovery tool

that is powered by freeform, natural language search that makes data discovery faster, more intuitive,

and more interactive for retailers in every major retail segment, including food, department stores,

discount stores, speciality, electronics, pharmacy, category specialists and home improvement retailers.

The search for customers, products and profit

Since 2008, the retail sector has been hit by three challenges:

A global recession has zapped consumer confidence – so customers are spending less

Competition within the retail sector is fiercer than ever. Retailers are focused on finding new ways to

differentiate their outlets, products and overall customer experience to appeal to traditional and new

customer bases. The saturation of home markets means that many retailers are turning to emerging

overseas markets. Whilst this globalisation provides new revenue opportunities it results in new pools of

suppliers, customers, systems and data that only adds to the complexity of the business.

The economics of rents and balance-sheets haven’t adjusted to account for reduced

consumer spend – so profits have been hit

The retail industry has always relied on operational efficiency to support growth and profitability, but

now more than ever this is a key factor. Retailers now have a choice of multiple channels through which

to sell their products, and balancing store-front with online operations requires continual adjustment to

forecasts, products and service offerings. Globalisation is also a key component of today’s supply-chain

with complications that include duties, customs and compliance with international regulations.


Sales channels have diversified whilst consumer knowledge has increased signifi-

cantly – so there’s more competition for custom

The diversification of retail sales channels, whilst creating an opportunity for growth and expansion into

new markets, adds significant complexity to the retail landscape. Multi-channel retailing creates a vast

array of potential customer interactions in-store, on-line, via TV shopping networks, direct mail and even

airport retail. Consumers can research products through one channel and make a purchase through

another so understanding this behaviour is critical to multi-channel success – and with the proliferation

of online retail (e-tail), consumers are more powerful and discerning than ever before.

There is little that individual retailers can do to impact the global economy, however it is well within

the power of organisations of all sizes to keep pace with a constantly changing environment in

order to attract customers, stay competitive and remain viable.

Swamped by data but still seeking insight?

Faced with the challenges outlined in the previous section, there is no disputing that Business

Intelligence is critical to retailers who handle immense amounts of information relating to supply chains,

to sales information, to store operations – and everything in between.

As a retailer, you will have invested heavily in BI platforms already, with a range of data warehouses,

databases and applications such as ERP, CRM, HR and financial systems. With this mountain of data

at your disposal, identifying the most valuable information can be extremely difficult. Even more of a

challenge is the ability to access specific data when you need it, get it delivered in the right way, and at

the right time to impact critical decision making.

To really derive value from their Business Intelligence, retailers must overcome a number of BI obstacles.

Harnessing big data

Over the past few years we have seen leading digital e-tailers employ big data analytics to create a

superlative experience for their users, and increasingly, multi-channel retailers are looking to follow

suit. The reason is simple; the decision-making journey of today’s empowered customers is increasingly

collaborative and interactive:

• 70% of customers consult online user reviews before purchasing online or in store - there are over 5 million customer reviews on amazon.com alone

• 65% of in-store luxury purchases are influenced by a digital experience, while 60% of online luxury purchases are influenced by the in-store experience

• 44% of mobile users check prices while they are in-store

• 60% of consumers following a brand on Facebook are looking for offers and coupons

Source: McKinsey’s Chief Marketing & Sales Of f icer Forum, 2013


Retailers need to stay ahead of consumer demands and insight is critical for innovation of product

offerings, pricing and promotion, channel strategy, store concepts and store locations. To do this requires

tools that can derive appropriate, timely information from a range of data types as illustrated in figure 1.

Structured data Semi & unstructured data

DATA DISCOVERY

NAME ADDRESS

AMOUNT DATE OF BIRTH

TRANSACTIONS

LIKE

TWEET

PRODUCT REVIEWLOYALTY POINTS

£

Overcoming data silos

Retail data easily reaches multiple terabytes when considering a data ecosystem that stretches across

stores and headquarters. This data is frequently constrained by silos – not just in terms of the location

of data in different databases or data warehouses, but also by diverse applications such as ERP, CRM,

financial systems and HR systems – see figure 2. In addition to system and application silos, many

business users rely on spreadsheets for their own analysis and whilst they could be valuable to a wider

audience, these Excel islands remain distinct from the corporate business intelligence set.

To get a more complete picture of the retail landscape requires these data sources to be readily and

easily integrated into a virtual data pool providing visibility and the potential to explore data associations

that may otherwise be hidden and untapped.

In addition, a retailer will have people in different locations that need to use this information for a variety

of purposes – from simple consumption of dashboards, to the ability to search, explore and discover

new trends.

Increased globalization further complicates the data silo challenge with a growing and distributed set of

operational information systems to monitor and manage.

Eradicating the time warp

Traditional business intelligence tools excel in analysing and reporting information in a set structure at

a given time. But all too often these reports are stale by the time they are published, and amending the

reporting or adding in a new piece of data is likely to add to the IT workload and result in further delay

so managers frequently complain of data fatigue.

Figure 1. Analysing

structured and semi-

structured data enables

retailers to derive new

insights


Research studies show that 75% of Business Managers are facing shrinking ‘decision windows’ so to

make the most of the opportunities available, today’s retailers are seeking real time data for agile

business decision-making. For example, with the ability to monitor the results of a promotion minute-by-

minute retailers can make informed adjustments that immediately and significantly impact on revenue

and the profitability of the initiative.

Comparing Traditional BI with Visual Data Discovery Tools

Visual Data Discovery: more than a pretty face for retail intelligence

According to Gartner, visual data discovery tools are the fastest growing segment within the BI &

Analytics toolkit: supporting business agility through self-service BI.

The freedom to search and explore

The biggest distinction between traditional business query tools and visual data discovery tools is the

degree of business user autonomy they enable. Whilst all data discovery tools are designed to enable

users to explore data from multiple data sources and a variety of different platforms, tools vary in

degrees of usability.

The NeutrinoBI visual data discovery tool has been designed from the outset to be the most intuitive

tool for business users. Powered by a freeform, natural language search engine, individuals are able to

simply type in a question to retrieve a set of relevant, ranked, visual results relating to their search in a

matter of seconds. So users can ask today’s question – to get today’s answers.

Source: Aberdeen Group 2012: Self-service BI through Data Discovery and Visualization

Traditional BI Reporting – business

managers are often involved in scoping

the reports, but this style of reporting

is predominantly controlled, driven,

and delivered by corporate IT. In

many cases only static views of data

are available and any changes or

enhancements must be made via the IT

organisation.

Visual Data Discovery – business

users are provided with rich, highly

interactive visual tools that speed up

the time to insight by allowing them to

manipulate and explore information

directly. Although corporate IT is still

involved, especially in the initial stage

of data mapping, the responsibility

for searching, creating and accessing

different views of the data falls upon

the business community.

VS


Exploring data is simple. Users can drill down to the underlying data tables, visually combine graphs into

one, add calculations, additional sources such as local Excel spreadsheets, and create their own

dashboard reports to publish and share with the wider organisation.

Accelerating discoveries through cool, clear visuals

According to a TDWI survey1, business users spend two-thirds of their time analysing data in tabular

versus chart form. Whilst this is an appropriate method for precisely analysing stock availability, a more

innovative visual format is required to help with identifying purchase patterns, consumer trends, and

supply-chain anomalies. Research has shown that when data is represented graphically, we use less

cognitive resources to make a decision and retain information better. So the graphs provided by Visual

Data Discovery tools are more than just pretty or engaging; it’s about speeding up the time to insight.

What’s more, visual data discovery tools are now available across platforms including desktop,

laptop, tablet and smartphone to enable real-time insight anytime and anywhere - no matter how

geographically dispersed your organisation.

Type a question to

retrieve a set of relevant,

ranked, visual results in a

mat ter of seconds.

1 The Data Warehousing Institute - Visual Reporting and Analysis: Seeing is Knowing


Increasing efficiency and enhancing ROI

A study by Aberdeen Group in 20122 found that on average, organisations using visual data discovery

tools were able to support 65% more BI users for every full-time equivalent employee involved in the

implementation of BI projects. Empowering users with self-service data discovery capability frees IT staff

from the steady stream of requests to tailor reports, modify dashboards and provide ad-hoc information

– enabling them to focus on the strategic BI infrastructure.

The Aberdeen Group Survey also reports that companies with visual data discovery tools are more agile:

• In 92% of cases, managers are able to find the information they need, when they need it

• It only takes 2 days to design and build a new dashboard, compared with 39 days for standard BI tools

• They can achieve ROI in less than half the time of traditional BI projects

Identify purchase

pat terns, consumer

trends, and supply-

chain anomalies with

a range of interactive

visualizations.

Search, discover, and

share actionable insights

in just under ten minutes

without requesting help

from IT.

2 Aberdeen Group – Agile or Fragile? Your Analy tics, your choice


Applications of visual data discovery tools in retail environments

Retailers can use visual data discovery tools such as NeutrinoBI in many ways, delivering insight

across multiple applications in both retail storefront and headquarter environments and here are a

few examples:

(For more examples refer to the dashboard gallery available at: www.neutrinobi.com/retail data discovery)

Store Operations

Using visual data discovery tools Store Managers, Regional Managers and Sales Directors can directly

analyse sales, promotion, inventory and store by store scorecard data. Receiving real-time dashboard

insight of KPI performance enables users to search and explore for additional insight into anomalies

and spikes.

The example dashboard below shows a visual scorecard of sales per square meter when comparing

a number of stores and branches.

Business benefit: store managers can access and explore information in time to make actionable

decisions that optimise the layout, product mix, resource efficiency and productivity of each store.

Sales Channel Analysis

Marketing and Sales Managers may wish to contrast online e-tail with in-store sales or compare

different reseller outlets to determine which selling-motions, products and promotions work best for

different customers’ purchase patterns.

The dashboard below contrasts online sales with in-store sales of digital cameras.


Business Benefit: Marketing and Sales Managers can react quickly to capitalise on changes in trends

and purchase patterns.

Customer Behaviour Analysis

By integrating multiple BI sources into one virtual pool of data, retailers have the ability to track and

analyse consumer behaviour in relation to the environment, product, service and price of sales. This in

turn opens the way to delivering individual customer experiences and the ability to guide consumers to

cross-sell and up-sell opportunities.

Business Benefit: Business analysts can visualize the insight needed to attract new customers or grow

the existing customer base.

Merchandise Management

Retailers can gain greater insight into the seasonality of products, effectiveness of promotions,

placement and price through analysis of sales and customer data. The dashboard below shows the

average transactional price for digital cameras over time, and could be used to evaluate promotion

effectiveness by item, category, geography and reseller.


Business Benefit: Buyers can monitor and test all aspects of the merchandising process including

returns, performance analysis, financial planning and space allocation.

Supply Chain Analytics

Analysis of sales and inventory data means you can improve purchasing and product management to

increase revenue and customer satisfaction. The dashboard below provides real-time insight into stock

availability and highlights potential risks.

Business Benefit: Supply Chain Managers can monitor inventory levels, optimize stock, reduce

shortages and lower costs by analysing stock movement through warehouses and stores.


NeutrinoBI – visual data discovery powered by freeform search

NeutrinoBI is the first of a new generation of Visual Data Discovery tools that enhances self-service

agility with its revolutionary freeform, natural language search capability. NeutrinoBI is the most intuitive

and interactive data discovery tool available and has been developed with IT Managers and super fast

implementation in mind. The solution is consistently deployed in less than a week so your team can

immediately start to address your BI challenges.

NeutrinoBI is available to use on your desktop, via a wide range of mobile devices and as a cloud-based

self-service BI solution. With our unified interface, the user experience is exactly the same - no matter

how the solution is delivered.

So from Store Managers and Sales Directors, to Buyers and Marketing, Product and Supply Chain Heads,

using NeutrinoBI your team can harness and examine data from disparate sources in retail storefronts

and headquarter environments - and turn it into actionable real-time insight.

It’s the BI advantage retailers have been waiting for…

To discuss the benefits of visual data discovery in the retail environment in

more detail contact Andrew Watson at NeutrinoBI:

Discover more.Faster.Discover more about NeutrinoBI, call +44 (0)121 222 5772 or email [email protected]

Documents

The retailers guide to data discovery - EM360 · 5 The retailers guide to data discovery // Whitepaper Retailers need to stay ahead of consumer demands and insight is critical for