December 1st, 2017

BIG DATA & ANALYTICS

TURN INFORMATION INTO ACTIONABLE INSIGHTS

Marcus Hartmann

Bisnode Group Director AnalyticsManaging Director SWAN Insights

Less than 0.5% of all data we create is ever analysed and used.

Source: MIT Technology Review

BIG DATA, NOISE & UNLOCKED INSIGHTS

0.5%

BIG DATA DRIVES CHANGE AND…

Unstructured data from social networks, websites and forums.

Text, images, videos, links, unrelated and incomplete.

Requires unstructured database and new science.

…CREATES MANY OPPORTUNITIES

Big Data Use Cases 2015 – Getting real on data monetization

- 12 -

Figure 4: Which problems/challenges would you like to address with big data technologies?

(n=431)

IT (45 percent) and management (43 percent)

top the list of thought leaders and drivers be-

hind big data in enterprises (Figure 5). The re-

maining business departments are still very

passive as a whole and are driving the topic

considerably less often. We, too, can confirm

this based on experience from our own projects

with clients. In many cases, either IT uses and

suggests big data technologies as a solution to

address old or new challenges from the bottom

up or management has recognized the strategic

benefits of digitalizing and using data and is

driving the topic from the top down. But enter-

prises can only ensure the long-term success of

big data when other departments accept and

utilize it. There is obviously still work to do in

this regard.

Upon closer examination, the data shows that

management is a decisive factor for the pro-

gress of a big data initiative (

Figure 6). In 61 percent of companies where

management is the thought leader or driver be-

hind this topic, big data initiatives are already

integrated in business processes. If big data ini-

tiatives are in pilot stage or conceivable in the

future, management is the thought leader in

only 46 percent and 34 percent of cases re-

spectively. What is also striking is that respond-

ents named operational departments such as

sales more frequently when big data is already

firmly anchored in their business processes.

57%

55%

51%

50%

46%

31%

27%

23%

19%

6%

1%

Analysis of large volumes of data

Better or new data analysis possibilities

Building predictive models

Analysis of information from differentdata sources (polystructured)

Faster delivery of data for analysis

Acceleration of decision-making

Monitoring/Analysis of streamingdata/Complex Event Processing

Better cost-benefit ratio for analyticalenvironments

Automation of decision-making

There are no pressing challenges inour company

Others

Embeddedreal-timecognitivetechnology

APIintegration;

Prescriptiveanalyticalmodels;Automateddatapreparationprocesses;

Changeofbusinessprocesses;AdvancedAnalyticsasaService

…

One-OffexperimentalBigDataAnalyticsEco-System

Highperformancedatamanagement;Predictiveanddescriptivealgorithm

Semi-automatedpredictiveanalytics

Scorecardsanddescriptiveanalytics

2020

2000

CustomerProjects ProcessandSystemIntegrated

StructuredData UnstructuredData

PROJECTSCOPE

NEEDS VISION

CONSUMERS AND CORPORATES LEAVE DIGITAL FOOTPRINT EVERYWHERE.

Consumers and Company are online and leave information about themselves scattered everywhere on the Internet.

How can we find those isolated footprints and reconstruct a consistent profile?

This is where Contextual Intelligence helps.

A HUGE POTENTIAL LIES IN ONLINE DATA

CONTEXT IS WHAT TURNS INFORMATION INTO INSIGHTS.

Information is scattered everywhere, and unrelated. The key is to bring in the outside world after separating the wheat from the chaff.

… and to connect dots between data and contextualize information in order to deliver insights that truly matter.

BRING CONTEXTUAL INTELLIGENCE TO DATA

Worldwide news Social data Open data Closed data

Millions ofRSS feeds

Profiles, posts,connections

Nearly everythingcan be found

Purchased ornegotiated data

CONTEXT

BENEFIT FROM THE POWER BIG DATA

ENRICH

Context mining Artificial Intelligence Network ScienceCreate new information

by connecting dotsLeverage data to let

machines take decisionsUnreveal hidden insights

through mathematics

QUALIFY TARGET DETECT REFINE PREDICT REVEAL CLUSTER EXPLORE

HOW CONTEXTUALINTELLIGENCE CAN HELP?

CONSUMER DATA ENRICHEMENTWITH ONLINE INFORMATION

Matching and data enrichment based on web social profiles.

1. Professional profiles

2. Social profiles

3. Affinities

4. Clustering enrichment

5. Enrichment from company websites

PREDICT CONSUMER MOVES FROM CALL DATA RECORDS

Customer challenge:

Wanted to know if customer will move to another location and change provider.

Bisnode solution:

• Analyzing numbers calling and numbers called creates a network;

• Network science predicts future customer moves from one city to another, based on network calls.

RANKS LEADS FROM CRM AND IDENTIFIES THE MOST VALUABLE CUSTOMERS

Customer challenge:

Thousands of leads in CRM – too much work to call them one by one.

Bisnode solution:

1. Leads ranked and sorted by the propensity to buy the car;

2. Lead's relationship with competitive car models;

3. Detailed characterization and enrichment of existing CRM contacts.

PREDICT RESIDENTIAL CUSTOMERS AT RISKOF CHURNING

Customer challenge:

High residential customers churn rate –wanted to know which ones will be at risk in the future.

Bisnode solution:

Customer ranking sorted by the propensity to leave the operator;

Customer data enriched by web information and characterized in classes;

Advices on the best way to run preventive campaigns to reduce organic churn.

THANK YOU

Marcus HartmannBisnode Group Director AnalyticsManaging Director SWAN Insights