using gis to enhance customer experience
TRANSCRIPT
Using GIS to enhance the Customer Experience
Meet your customers where they live
Gary Allemann
Why Customer Experience Management?
• New Products or Pricing models quickly nullified
Why Customer Experience Management?
• Poor service or unhappiness easily made public
Why Customer Experience Management?
Product/ Pricing
ServiceCustomer Experience
“the practice of designing and reacting to customer interactions to meet or
exceed customer expectations and, thus, increase customer satisfaction, loyalty and
advocacy”Gartner
How and where does our customer interact?
Big data promises to answer these questions
• Who is our customer?• How do they interact with
us?• Which channel do they
prefer?• How do they buy?• Where do they interact?
What is big data?
Big data provides new insights quickly by simplifying the processes of combining and analysing data of any type and any size.
Big data is characterised by any combination of:
• Variety• Volume• Velocity
Case Study: Insurance
Case Study: Fraud Detection
Geolocation
Transaction
Point of Sale
$$$$$
$$$
Case Study: Telecommunication
With the new insight generated through big data analytics, this telecommunications company gained a complete view of its customers and which mobile towers are being used by power users.
As a result they saved over hundred million dollars in network optimization, by upgrading the towers that are mostly used by power users.
Location Data
Subscriber Demographics
Network Performance
Case Study: Government
“To accelerate the eradication of poverty in South Africa through the use of enabling technologies that support the
improved planning, targeting, co-ordination, and delivery of anti-poverty services.”
What we received
Multiple spelling variations (similar sounding phrases)
English and Afrikaans Addresses
Many variations e.g.Township, T/ShipA/A, Admin AreaSq/camp, Squarter
Camp
e.g. +- 300 variations of East London
Standardised Address
Actual vs Theoretical Beneficiaries per Local Municipality
Identify areas with large disparities between theoretical and actual beneficiaries.
Nelson Mandela Bay: Theoretical 126,670 vs Actual 159,772 (METROPOLTAN)
Engcobo: Theoretical 73,221 vs Actual 45,389 (RURAL MUNICIPALITY – Chris Hani District Municipality) Camdeboo: Theoretical 14,046 vs Actual 3,472 (Cacada District Municipality)
Example 2 – Coverage of Clinics & Hospitals
Hospital / Clinic
Bridging the gap
Bridging the gap
Bridging the gap
Questions?
+27 11 485 4856
@Gary_Allemann
http://www.linkedin.com/company/master-data-management
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