2. Content
Are you a Big Data believer? Page 3
Data, data everywhere Page 3
New data sources are appearing all the time Page 5
So, where to start? Page 6
Short term rewards reap long term gain Page 7
Where to begin your Big Data journey? Page 7
To data infinity … and beyond Page 8
About Paul Hinds Page 9
3. Are you a Big Data believer?
Do you remember when CRM was the next big thing? It was supposed to deliver ultimate customer
engagement. In reality, it was all about software; and very expensive software at that.
Sure, these expensive CRM software solutions did deliver a certain amount of segmentation, but they
generally did not get to the heart of the issue – that the data itself was generally not very good in
terms of quality.
So what about Big Data? Is it the new CRM; the next Dot-com; the big brother of Web 2.0? If Google
search data is anything to go by, maybe not:
What the Big Data debate has done is ensured that Some organisations have been doing this for years,
data itself has caught up with the aspiration of what but Big Data is all about doing it better and using
businesses would like to do with it. Technology is data to positively impact the customer.
now truly an enabler to achieve this, both in the
‘back office’ environment (which is increasingly in Data, data everywhere
the Cloud) and direct customer touchpoints, such as
mobile Apps. We are closer than ever to having truly The key challenges are the explosion of data and
personalised customer engagement and how to collect it. The rapid emergence of new
relationships. payment methods, such as mobile wallets, together
with digital technologies, have revolutionised a
Big Data, however, is nothing new. It’s simply about business’s relationship with its customers. Long
joining the dots of all the relevant data sources. gone are the days when loyalty cards were the only
Whether it is customer data, local market data or way to identify and collect customer data.
communications data, every company out there has Increasingly retailers are using their online customer
at least one data source at its fingertips. base as the equivalent of a loyalty scheme – they’re
Page 3
4. using the same data and channels without the need huge increase in direct customer interaction and
to maintain a separate currency for loyalty. feedback. For those who have been slow to
embrace the brave new online world, the rise in
Today, with multiple ways to identify a customer social networks has been a rude awakening. Many
across a growing number of channels, it’s all about are now being forced to re-think their online
Big Data; multiple data sources – both internal and strategies.
external – being brought together to put the
customer at the heart of business strategy. Amazon is something of a poster child for Big Data.
They have, in essence, a very simple data model.
Businesses everywhere are under pressure to better They don’t have stores and they don’t have a loyalty
understand, engage with and respond to their scheme per-se. Their version of Big Data uses the
customers. This requires data, and lots of it. The huge volumes of customer and payment data that
good news is that there is so much wonderful they have at their fingertips to personalise the online
behavioural data out there, ready and waiting to be shopping experience and offer products that are
put to good use. The bad news is that although the related to what their data tells them about the
opportunities for harnessing this data are pretty lifestyles and preferences of their customers.
much infinite, the issues are also increasingly
complex; particularly as the journey from need or Along with ebay they have set the standard for
desire through to purchase becomes less providing a forum for sharing customer feedback on
predictable than ever before. Analysing your data products (and now partner retailers) and measuring
and quickly acting on the resulting insight is, customer satisfaction.
therefore, crucial. Just knowing what a customer
bought, whether a product or a service, is no longer They grow their data asset still further by prompting
enough; businesses need to understand long term customers to share more information and confirm
consumer behaviour, what customers are doing the intelligent assumptions that they make based on
before or after they make their purchase, and what statistical models. Just glancing at my one ‘Amazon
their interests and aspirations are. Betterizer’ page shows how well they know me from
mining their version of Big Data - they know I am a
Digital channels have added a whole new dimension parent, where I have been on holiday and target
to the data debate, with new streams of ‘live’ data incremental spend by offering further categories for
coming direct to a company from their customers. me to shop in:
The advent of social media in particular has led to a
Page 4
5. New data sources are appearing all the time SpendographicsTM which we’ve developed in
partnership with Visa Europe, helps businesses to
In addition to all the data now being generated understand their customers on the basis that ‘they
through digital touchpoints, new commercial data are what, where, when and how they spend’ – a
sources are also available which bring a third monumental departure from the traditional and,
dimension to customer insight. Previously, some would say, outdated geo-demographic profiles
businesses have been able to use their data to see generally used to drive customer segmentations.
which customers are shopping through their stores
and channels, and which of their products they are This new segmentation tool improves the resolution
buying. at which consumer behaviour can be analysed and
works at a market, brand and sector level.
A recurring challenge is how to accurately determine Individuals are grouped into 10 different “spender
what their customers are doing when they’re not modes”, which comprise people with similar
shopping with them. Which of their competitors are characteristics and behaviours who can be
also on their shopping list? How frequently and how communicated with in a consistent and targeted
much are they spending with other brands? What manner. The segments have been given a name,
does this behaviour say about their customers in tagline and pen portrait to help understand their
terms of preferences, lifestage, purchasing power spend behaviour and how to engage with them. This
and brand loyalty? insight can be used to improve business
performance at both strategic and tactical level.
URBAN SPENDERS WORK HARD, PLAY HARDER
CARD USE: 5 TIMES A WEEK
SPEND BEHAVIOUR
SALES METRICS CARD TYPE
ATV £26 CREDIT 3%
AV. AV.
97%
ANNUAL SPC £6,908 DEBIT
AV. AV.
INT’L SPEND 2%
AV. COMMERCIAL 1%
AV.
POS CHANNELS
64% 26% 10%
59%AV. 22%AV. 19%AV.
3% 4%
CARDS - 1.9M OF 68M SPEND - £12.8B OF £335B FACE TO FACE ONLINE MAIL / TELE
ORDER
Urban spenders are very active, using their card a large amount (especially in the SHOPPING HABITS
TOP THREE SECTORS BY SPEND
afternoon/evening) for both cash withdrawals and card transactions across a wide
range of merchants. Being commuter-types, they spend a significant proportion of their 8%AV. 18%AV. 3%AV.
budget on TFL and rail tickets. Their social agenda is packed and these spenders often
frequent bars, restaurants and clothes shops. They enjoy a high quality of life and are
therefore likely to go to a gym or health-club and although they spend less than others
in supermarkets (possibly because they like to eat out), when they do they will visit the
high-end grocers. They are also active online and use their cards with online retailers
ENTERTAINMENT SUPERMARKET TRANSPORT
and budget airlines.
15% 14% 14%
LIFESTYLE INDICATORS
TOP THREE SECTORS DIFFERENTIALS
MORE LIKELY TO... LESS LIKELY TO...
COMPARED TO THE UK TOTAL, THESE CARDHOLDERS
ARE MORE LIKELY TO SPEND MORE IN THE AREAS //
WHERE CAN YOU FIND THEM
BUDGET HOME SOCIAL YOUTH MATURE 8% 6% 3%
IMPROVEMENTS ORIENTED MARKET
15% 8% 14%
ENTERTAINMENT CLOTHING TRANSPORT
24* 8* 6*
HAVE A CAR HAVE A PET HAVE KIDS GYM MEMBERSHIP CITY
SPENDERS
* NUMBER OF DIFFERENT BRANDS WITHIN THIS SECTOR
SPEND BEHAVIOUR SHOPPING HABITS
SALES METRICS CARD TYPE 8%AV. 18%AV. 3%AV.
ATV £26 CREDIT 3%
AV. AV.
97%
ANNUAL SPC £6,908 DEBIT
AV. AV.
INT’L SPEND 2% ENTERTAINMENT SUPERMARKET TRANSPORT
AV. COMMERCIAL 1% 15% 14% 14%
AV.
Page 5
6. Collecting, interpreting and acting effectively on your So, where to start?
customer data can be a real differentiator in terms
of developing positive customer relationships and It’s not as hard as some are making out to make Big
loyalty. It can provide the best possible competitive Data deliver a quick return for your business. The
advantage; it is your chance to make sure that you mistake many companies make is trying to bring all
put their needs at the heart of your decisions around of it together, all at once.
product, price, place, promotion and people (yes,
that old marketing classic). Take the time to understand what your version of Big
Data needs to look like for your company and your
customers; then pick one area of focus and put your
energy and resources into that.
From this...
PRODUCT DATA www.
Brand Style type
Home
etc.
Purchases Reviews Searches
Warehouse
Store COMMUNICATIONS
LOCAL MARKET DATA AND PROMOTIONS
Geography housing Online Customer behaviour
types competitors
Financial Sales
Customers
Customer Care
CUSTOMER DATA
www.
Voice of the Payment Cards
Basket and trolley
PRODUCT DATA Customer
data overtime
Brand Style type
Home
etc.
Purchases Reviews Searches
Service and product.
Feedback and opinions Feedback, reviews
price comparison
Focus group Loyalty Cards
E-mail, Address, Name
To this...
Warehouse
LOCAL MARKET DATA
Geography housing
Store COMMUNICATIONS
AND PROMOTIONS
Online Customer behaviour
types competitors
PRODUCT DATA www.
Brand Style type
Understand what your version of
Home
etc.
Financial Sales Purchases Reviews Searches
Customers Big Data needs to look like for your
Warehouse
LOCAL MARKET DATA
Geography housing
Store COMMUNICATIONS
AND PROMOTIONS
Online Customer behaviour
business and your customers.
types competitors
Customer Care
Financial Sales
Voice of the CUSTOMER DATA Payment Cards
Customer
Customers Basket and trolley
data overtime
Customer Care
Voice of the
CUSTOMER DATA Payment Cards
Basket and trolley
Service and product. Customer
data overtime
Feedback and opinions
Focus group Loyalty Cards Feedback, reviews
Service and product.
Feedback and opinions
E-mail, Address, Name Feedback, reviews price comparison
price comparison
Focus group Loyalty Cards
E-mail, Address, Name
Page 6
7. Short term rewards reap long term gain These offers were delivered to customers in 32
different campaigns over 8 weeks.
Although true customer loyalty is about long term
retention and engagement, in today’s challenging The results have been astonishing: an overall
economic environment retailers need to act fast to redemption rate of 13% across all campaigns, with
entice new customers and win back the lapsed. some cells getting as high as 54%. We won back 3%
Customers are less and less likely to wait around for of customer who had not visited a store for 6
their reward; they want instant recognition and months. And we identified the categories with the
gratification. The trick for retailers is to deliver this best opportunity for retention.
loyalty kick without devaluing their brand offering.
We all know of high profile retailers that are all about Interestingly, new media channels were a key
discounts and vouchers; savvy customers will rarely component part of the success of these campaigns,
buy from them at full price when you can search including the use of optimised barcodes for SMS.
online for a 20% off code. And it doesn’t end there; the results of these
data-led tests have formed the foundation for the
For example, Beyond Analysis is working with a business case to apply the benefits of insight to all
leading South African retailer to use their loyalty areas of the business, from promotions to store
scheme differently in order to: merchandising.
- Drive more spend and visits from their top This is the power of data in action.
shoppers
- Win back dormant and lapsed customers, and Where to begin your Big Data journey?
- Ensure customer retention in key categories and
locations
We used customer behavioural data to construct
campaigns which were both relevant to customers
and met the client’s strategic objectives. Using 12
months’ worth of data, we undertook a customer
behaviour analysis, identified core target segments
and built tailored offers to meet their needs.
Here’s the Beyond Analysis 6 point plan for getting started:
1. Be clear on your business objectives, and those of your customers
2. Understand what data you have right now (and what you don’t)
3. Align 1 & 2 and then create your own Big Data plan
4. This should NOT be a 3 year, all-singing all-dancing plan; plan in detail for the first 12 months, then
in high level for years 2 and 3
5. Only include actions that can be tested and measured – so you can learn and develop proof points
6. Be committed to your data; if you’re in it for the long haul, so will be your customers
Page 7
8. To data infinity … and beyond
The future is about intelligent customer
engagement. It’s about marketing to and engaging
with the individual. To achieve that, we need to
know what customers think, and to understand what
they do and why. In order to know all that, we need
to listen.
In today’s challenging and competitive economic
climate, we must reassess whose views matter. Our
employees, partners and customers could just be
the best people to tell us how to make our business
succeed.
Do it right and do it consistently, and loyalty and
engagement will be the happy result.
Page 8
9. About Paul Hinds
Since graduation Paul has spent the majority of his
professional life working in data insight consultancy
and customer strategy.
His core skills centre upon strategy development,
programme design and stakeholder engagement
with the focus on delivering actionable insight that
make a tangible difference to the organisations with
which he works.
Paul is passionate about ensuring Beyond Analysis
does everything possible to enhance client
understanding of their customers and maximise the
value of their data asset to provide relevant
information that has a meaningful commercial
impact.
In his spare time Paul can be found persuading his 3
year old son Lucas that Liverpool FC are the team he
should be supporting and serving charred meat at
family barbeques, whatever the weather.
Page 9
10. Author
Paul Hinds
E-mail
paul.hinds@beyondanalysis.net
London office
0208 875 7099
Please contact Paul Hinds for further information about the paper and for enquiries regarding how Beyond
Analysis can help your business.
About Beyond Analysis
Beyond Analysis is a leading customer insight and strategy business. We believe that the customer should be
at the heart of everything we and our clients do. And we’re passionate about using the power of data to
achieve this: finding it; collating it; interpreting it; unlocking its value.
We work with some of the world’s largest consumer brands to harness the power of their data and adopt a
customer-led approach to their decision making. We bring together multiple data sources to interpret
consumer trends and give our clients a clear line of sight to help them grow their business.
We have offices in London, Sydney, Singapore and Denver.
Beyond Analysis Limited. Registered Office: Unit 10 - 12, 116 Putney Bridge Road, London SW15 2NQ
Registered in England. RGN: 06059028
T: +44 (0)20 8875 7020 W: www.beyondanalysis.net F: +44 (0)20 8875 7099
Page 10