Using personalisation and analytics to drive better results

TO DRIVE BETTER RESULTS
PERSONALISATION
ANALYTICS
ANDUSING
TO DRIVE BETTER RESULTS
PERSONALISATION
ANALYTICS
ANDUSING
By Digital Alchemy Team

2Copyright © Digital Alchemy USING PERSONALISATION AND ANALYTICS TO DRIVE BETTER RESULTS
1
IBM Center for Applied Insights. 2013. The State of Marketing
2013, IBM's Global Survey of Marketers. [Online].
Available at < http://www-01.ibm.com/software/market-
ing-solutions/campaigns/surveys/2013-marketers-survey.html>
[Accessed 7th
September 2015]
Consumers are creating their own personal
experiences online and expect the
brands they interact with to provide high
personalisation standards and to participate
with them in shaping these experiences.
People are not just benchmarking against
the market leaders in one industry but all the
organisations and brands that serve their
needs. The online public rightly expects
everything to be available on demand and
loyalty can be won or lost in a moment.
For many businesses this is where customer
analytics steps in, taking marketing to a
new level and enhancing ROI. Organisations
are all at different stages of development
and preparedness, however, an analytics
capability is an increasing priority. It sustains
real competitive advantage by transforming
customer data into actionable insights and
facilitates real-time personalisation. IBM’s
Global Survey of Marketers1
in 2013 found
that the top 20% of Leading Marketers
surveyed were leveraging the power of
real-time personalisation, adjusting real-time
offers based on context by a factor of 2.6
compared with all other marketers.
MINING THE GOLD IN YOUR CUSTOMER DATA!

With the availability and choice of so many
different points of access - mobile, online,
call centre, retail, etc. - customers need
to be engaged at every touch point with
the same intimacy and personalisation,
regardless of the channel. Taking analytics
further, this means that systems must be
able to learn from behaviour across multiple
channels and update messages and
offers accordingly if they hope to sustain
customers’ engagement.
Current consumer-facing technologies
that demonstrate a similar type of system
learning are the intelligent personal
assistants like Google Now. Their attraction
lies in the ability to pre-empt users’ desires
and needs. The Apple Watch meanwhile
uses more personal data, such as biometric
health information, in order to create a more
meaningful ecosystem around the wearer.
ADAPTING TO DIGITAL ERA
2
Vizard, S. 2015. M&S promises personalisation push to boost
online sales. Marketing Week [Online].
Available at <http://www.marketingweek.com/2015/05/20/
ms-promises-personalisation-push-to-boost-online-sales/?no-
cache=true&adfesuccess=1> [Accessed 5th
September 2015]
Clearly, there is no turning back now,
real-time personalisation is a continuous
journey of assessing, evaluating,
determining and learning.
In the retail space, according to Marks &
Spencer CEO Marc Bolland,2
M&S is trying
to improve website personalisation and
aspires to be “increasingly connected”.
They constantly look at new channels that
are “popping up”, like the Apple Watch,
to see how they can be used for improved
customer engagement.

PERSONALISATION
There is undoubtedly more to personalisation than getting the customer’s
name right. While personal data, demographics and purchase history offer
marketers a preliminary snapshot of individuals, only customer interactions such
as searches, website visits, mobile location and other touchpoint information
provide the means to fully leverage real-time personalisation.
Although customers are prepared to give away their information, they obviously
expect something in return. If customers are disappointed with their interaction
experiences and feel that relevance and value are missing, they will quickly
look elsewhere. While understanding customer needs, wants and preferences
are what every marketer strives for – context is the overriding thing.
Personalisation needs to be respectful and appropriate to the type of business
and nature of the customer relationship. Beware of overstepping the privacy line
and appearing “creepy”: conservative organisations like finance and insurance
companies need to be particularly mindful of this.

CAPTURING WEBSITE INTERACTION/ACTIVITIES
For organisation new to these procedures,
it is best to adopt a phased approach,
focusing first on major interactions that
have the potential to impact a known
business problem - such as abandoned
shopping cart transactions. Various tools
can be deployed to tag the website and
capture the data needed. Data points can
also be configured in the site to activate
next best offer or next best message when
customers hover over certain spots.
The ability to connect with people on their
own terms during those moments when
customers and prospects contact you can
dramatically improve the effectiveness of
your marketing efforts.
Room & Board, a US furnishing retailer,
introduced predictive intelligence to drive
next best offer via web browsing and
shopping.3
Of the people who engaged with
predictive content, 37% purchased from
one of the company’s channels, with 53%
of them purchasing from an offline channel.
This represented a significant increase in
both online and in-store sales.4
But be aware that integrating website and
social data can be tricky, especially as the
ownership often sits in separate business
units. A genuine customer-centric culture
helps to ameliorate these challenges, as
does a mutually agreed business plan with
clearly defined roles and responsibilities.
In addition, this can also be advantageous
to exchange some staff between the units
to encourage enhanced understanding,
communication and cross-fertilisation of ideas.
3
Milnes, H. 2015. How Room & Board uses digital data in its
physical stores. Digiday [Online].
Available at <http://digiday.com/brands/small-furniture-store-re-
warding-customers-reaping-rewards/> [Accessed 7th Septem-
ber 2015] and Saleforce. 2015. Customer stories: Marketing
Cloud Customer Success. [Video Online].
Available at <https://www.salesforce.com/marketing-cloud/cus-
tomer-stories/> [Accessed 7th
September 2015]
4
Heller, L. 2015. How Room & Board makes data personal.
Fierce Retail IT [Online].
Available at <http://www.fierceretail.com/retailit/story/how-
room-board-makes-data-personal/2015-04-15> [Accessed 5th
September 2015]

ANALYTICS
Insightful data analysis relies on appropriate quality data being aligned in a single
customer view that ideally encompasses transactional, behavioural, demographic,
service, and online browsing data, etc.
Many of the answers you need are simply buried in your database: the challenge
is to identify the most meaningful and telling patterns within the transactional data
streams and customer profiles. But be aware that data analytics is not just about
installing complex analytics software and hoping that you will eventually find a
valuable breakthrough. Analytics is an iterative process, it takes time to get right and
it continues to evolve, so don’t wait for it to be perfect, begin now and start using it as
soon as you can, then refine over time.
If analytics is the next step you need to take and you are attempting to get it
across the line, you can always get underway with your cross-sell strategy by
looking at the obvious touch points and interactions that indicate a customer is
likely to be in market. This is a great place to start, then overlay the predictive
models, etc., as they are developed and refine the contact strategy accordingly
through optimisation.
6USING PERSONALISATION AND ANALYTICS TO DRIVE BETTER RESULTS

THINK MULTIDIMENSIONAL
When looking at analytics for cross-sell and upsell, avoid making your models
one dimensional. Predictive models are great but also consider things like
propensity to buy, uplift models, the most likely time of purchase and so on.
These inputs will adjust your prioritisation and likely increase the lift. Start with
a clear idea of what you want to achieve and use this to guide and focus the
process. It’s also a good idea to ensure that whatever you build is applied
across different channels to drive a broader return on investment. Don’t just
focus on outbound, think how it can be used for inbound, online, social, etc.
This will also help with the business case.
And if you’re not yet ready to undertake real-time personalisation during
customer interactions, you can start with a pre-emptive strategy using
analysis to identify and prepare suitable offers in readiness for potential
customer contacts. Then over time, work towards the much more effective
alternative of making real-time personalisation decisions on the fly.

Also remember not to put all your eggs in one basket, don’t focus all your development
on predictive models alone. There are two ways to approach the sales process:
APPROACHING THE SALES PROCESS
From the customer perspective – i.e. what is the customer in the market for
right now. This can be done using next best offer engines that present the
optimum offers appropriate to a moment in time.
From the product perspective – i.e. who is likely to be in the market today for
the particular product you want to sell. This is where a predictive model can
be effective by looking at the likelihood to buy based on a customer’s buying
journey and the timing.
1
2

ANALYTICS IN ACTION
Target identifies sales opportunities through
data analytics of customers’ past purchases.
Predictive analytics help to determine whether
women are statistically likely to be pregnant
if they start buying unscented lotions and
prenatal supplements. Prospects are sent
coupons for baby products.
Walmart conducts data analytics on a real-
time basis by fusing data from past purchases,
internal stock information, mobile phone
location, social media and weather forecasts
to boost BBQ cleaner sales. If a customer owns
a BBQ, lives close to a store and the weather is
good, Walmart sends a voucher for a BBQ cleaner.

GROWTH THROUGH ANALYTICS
5
Gordon, J. et al. 2013. Big Data, Analytics, and the Future of Marketing & Sales. [e-book] McK-
insey & Company. Available at: McKinsey on Marketing & Sales <http://www.mckinseyonmarketin-
gandsales.com> [Accessed 5th
September 2015]
A McKinsey review of more than 250 projects over five years reveals
that companies implementing customer data analytics can improve
their marketing ROI by 15-20%.5
Achieving competitive advantage through analytics relies on the capacity
to predict the future before your rivals. Eventually our knowledge of each
customer and our understanding of their needs will be so detailed that they
can be offered solutions before they are aware of the need themselves.
That’s why you need to start the journey now - or risk being left behind.

Digital Alchemy Limited (DA) is Asia Pacific’s
leading Database Marketing Services Provider. DA’s
team of professionals are dedicated to working with
clients to improve their marketing efficiency and to
capture latent customer value. Established in 2003
and operating in Sydney, Melbourne, Auckland,
Bangkok, Hong Kong, Nanjing, and Singapore, DA
has been contributing to the success of an expanding
breadth of clients including leading companies
in financial services, telecommunications, retail,
motoring services, media, and other industry sectors.
ABOUT THE AUTHOR
Digital Alchemy Team
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Using personalisation and analytics to drive better results

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Using personalisation and analytics to drive better results