Date: 14th November 2018 Location: Customer Experience Theatre Time: 14:30 - 15:00 Speaker: Ed Willis Organisation: Collect+ About: Collect+ is the UK’s largest independent store-based parcel delivery and returns service. It offers a simple and convenient way for people to collect online purchases from or return unwanted items to more than 400 high street and online retailers – all at their local convenience store. In this session Edward Willis, Head of Customer Marketing and Insight, will talk about using self-service analytics platforms like Alteryx & Tableau to map the store network and enhance the customers’ experience.

1. Spatial Analytics & Data Enrichment to deliver
consistent Customer Experience at Collect+
Edward Willis
Head of Customer Marketing and Insight
Collect+
14th November 2018

2. To be the best loved parcel service, delivering
freedom and convenience, not just parcels.
We’relisteners and innovators, developing better,
simpler solutions to meet your needs.
Weask why, so you don’t have to.
2Collect+
The Collect+ Mission

3. Our network growth
3Collect+
Strong store growth and consistent client
wins since 2009 mean that more and more
customers throughout the UK are benefiting
from the Collect+ service.
2011
4,721 Stores
128 Clients
2013
5,500 Stores
260 Clients
2009
3,429 Stores
8 Clients
2016
6,100+ Stores
350+ Clients
2017
7,000+ Stores
400+ Clients

4. Why Collect+?
4Collect+
90% 93%
7000+
COLLECT+
POINTS

5. Why Collect+?
5Collect+
400+
CLIENTS
93% 9.3m
PEOPLE IN THE
UK LIVE WITHIN
300 METRES OF
A COLLECT+ POINT

6. Serving Customers from Land’s
End to John O’ Groats
6Collect+
• 7,000 stores across the length and breadth
of the UK.
• We are the only independent network to
cover all of Wales, Scotland and Northern
Ireland.
• We cover ROI in our partnership with
Parcel Motel.

7. Collect+ is where customers are not just where they live
7Collect+
Shopping Centres Convenience Stores Forecourt Retail

8. Our customer experience driven by data and insight
8Collect+
• In a sector that only cares about parcels
and not people, CollectPlus is different.
• Providing excellence in our service and the
customer experience are things we are
proud to focus on.
• A sharper, faster and deeper focus on our
data, through analytics and insight means
we are able to be more customer
orientated.
• Listening to, and learning from, our
customers allows us to be their perfect
online shopping partner.

9. Alteryx changed how quickly and easily we were able to
analyse and report on our own data.
9Collect+
• Started using Alteryx in 2015.
• The earliest use case was to measure the
impact of a marketing campaign using
operational data and some bespoke
reporting from different agencies and
departments.
• We had all the data we needed, but not in
one place.
• We needed to understand the full impact
of what the campaign had delivered. What
had worked; when and why.
• Before Alteryx:
‒ Heavy reliance on sophisticated
spreadsheets.
‒ Query the data from multiple places
and build the results in Excel.
‒ Slow and time consuming.
‒ Very limited visibility and relied on the
analyst to communicate the process
and the logic.

10. Consolidating our data into one place allows us to better
understand our customers
10Collect+
• Alteryx allowed us to shortcut the whole
process, by getting to the same results in a
fraction of the time.
• We brought all of the data into one place
without having to spec and build a database
with IT or Dev time.
• Hours worth of calculations, look ups and
appends of data can happen in Alteryx in a
fraction of the time compared to our
previous approach.
• The community and the online resources
make learning the tool easy. Advanced Excel
users and SQL coders pick it up quickly.

11. • Mapping our network compared to a clients store estate
11Collect+
Case study

12. Case study: Mapping our network and calculating distance
12Collect+
• Problem:
‒ A prospective retail client asked how our store network could compliment theirs.
‒ They were keen to understand how they could best supplement their own network with a
third party pickup provider.
‒ With 30 stores in town and cities across the UK, they already had their own store estate.
• Our solution:
‒ Map out all 30 client stores and 7,000 Collect+ stores.
‒ Visualise the store network to illustrate on a map.
‒ Supplement the map with a filter on the distance from store to Collect+ point.

13. Alteryx: Calculating distance
13Collect+
• Our approach was to use Alteryx in combination with Tableau.
‒ Alteryx for the calculations and Tableau for the visualisation.
Our Alteryx workflow

14. Find the longitude and latitude of all the points
14Collect+
• With a few simple steps we were able to
reference the long and lat for all of our
stores and the all of the clients stores.
• Full lists of UK postcodes (all 1.9m of
them) are available online from several
free sources.
• We then cleaned each data source and
joined the long and lat data to each store
record.

15. Locate each point with Alteryx
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• Each data source was labelled with the
appropriate ‘Store’ name.
• Alteryx can then allocate a spatial point to
each record from our two flows, so that
this can be used in calculations like
distance.

16. Calculate the distance between spatial points
16Collect+
• We then append the
records into one data
set, so that client and
Collect+ data are in
one table.
• The distance between
each point is
calculated, before the
data is tided up and
ready for Tableau.

17. Mapping the output
17Collect+
• Alteryx saves the data back down to a
location where Tableau can reference it. We
then do our mapping tasks in Tableau.
• The output was used by the client to evaluate
how our network complimented their own.
• We were able to highlight which stores where
within 5 / 10 / 20 / 50 miles of their own
stores.
• This allowed the client to shape the
experience at checkout to best serve our
customers.
Collect+ stores in and around Birmingham

18. Mapping our network: Calculating distance
18Collect+
• Alteryx is quick. We saved hundreds of hours of effort on this one example alone.
‒ We find the long and lat for 7,000+ locations and calculate the distance between each of
them (210,000 records) in less than 30 seconds.
‒ Excel could not do this because of the size of the postcode data files.
‒ SQL can, but scripting this would have taken hours with IT / Dev support to manage the
data.
• No need for tech or dev time and no strain on our server too.
• Happy IT, Happy business, Happy client.

19. Data visualisation and Alteryx

20. Data visualisations from database to Alteryx and Tableau
20Collect+
• From individual store
reporting we consolidate this
into postcode districts and
then to a national view of
reporting.
• By using Alteryx and Tableau
in conjunction with our
database setup, we are able
to support the business in
the decisions making
process.
• Informational availability
allows for quicker, better and
more direct decisions to be
made.

21. Thank you.
Any Questions?
21Collect+