Customer Analy/cs for your Marke/ng Strategy

Transcription

1 Customer Analy/cs for your Marke/ng Strategy Carlos Alvarez Channel Manager, BIRT Analy2cs Division 1 Actuate Corporation 2012 June 5th, 2014

2 Data is a Game Changer 3

3 Today, Data is the Game Changer Key Drivers in 2014 and Beyond Driven by big data, digital adop2on, and customer loyal ini2a2ves, data is a key differen-ator in 2014 and beyond: Leaders want to be proac/ve Business analysts require beaer insights from large data sets from disparate sources To drive everyday business performance lower churn, beier target campaigns, iden2fy inefficiencies, reduce risk, etc. Do it In hours vs. days Do it without help from IT Do it without calling in the data scien2sts! The Data Driven World Predic-ve, advanced, analy-cs that deliver ac-onable insights to everyday work will drive the next wave of marke-ng and business op-miza-on 4

4 Customer-Centric Initiatives In the era of Big Data 5

5 It is not about Big Data, it is about Big Value Analyzing customer behavior is one of the most important goals of the Big Data era The explosion of new data sources that are available today enables companies to gain insights that were not possible before Big Data doesn t get tangible un-l you pick a problem to solve Companies seek new compe22ve advantages by resolving customer- centric problems such as churn, targe-ng, sa-sfac-on and risk as quickly as possible by adding, integra-ng and analyzing Big Data sources 6

6 Big Data Analysis is Customer- Centric Customer experience analysis Customer insights Marke-ng targe-ng / decision Capacity forecas-ng Behavioral analysis Customer lifecycle management Opera-ons improvement Network monitoring Fast analy-cs are essen-al to building a data- driven culture and delivering effec/ve campaigns and customer experiences. 7 Big Data is customer- centric and all over the place Data warehouses Web ac-vity logs Archived documents Census reports SAP, SFDC and Oracle Real- -me opera-onal processing systems

7 So Know Your Customer is KEY Customer analy-cs allow organiza-ons to make effec/ve decisions from the analysis of customer behavior. These solu-ons leverage market segmenta-on and predic-ve analy-cs to drive the right customer- focused strategies. The result: improved acquisi-on, reten-on, cross- sell/up- sell, and be_er, more targeted marke-ng campaigns. 8

8 Know Your Customer The value of customer analy-cs is proven, but it becomes only a real compe//ve advantage for those companies who are able: To do it faster, assimila-ng customer insights into business strategy as soon as it comes To seamlessly integrate whatever data source needed to get a holis-c view, no ma_er the origin or the size To add variables and enrich the data on the fly, geang different scenarios and point of views with no latency To extent the knowledge to key people in the organiza-on in an understandable way, enabling them to make faster and smarter decisions. 9

9 Fast analytics are essential to building a data-driven culture and delivering effective campaigns and customer experiences. 10

10 INSIGHT to ACTION Customer Analytics Marketing Campaigns Insight Action 11

11 Challenges of Building Data- Driven Marke/ng Strategies Access data Ever increasing volume and velocity of data Complexity of loading, cleaning diverse sources Need best view Understand paierns Profile and segment customers Look for trends, rela-onships Explore, visualize without coding Deliver insights Enable business users Integrate insights with opera-onal systems Create best offer fast! 12

12 Our Approach Easy Access and INTEGRATION To create a complete picture of customers, we need to combine insights from social channels and campaigns with Web and transac/onal data 10 Reasons 2014 will be the Year of Small Data, ZDNet, Dec 2013 Web CRM Social Other sources Columnar DB 13

13 Our Approach Reduced TIME to Value Many vendors are trying to (make predic/ve analy/cs available to an end user in a consumable form) but in our view BIRT Analy/cs comes closest to gezng it right, by not requiring the user to select algorithms IDC, Feb Columnar DB Explora/on & Visualiza/on Segmenta/on Analy/cs & Data Mining Profile Forecast Decision Tree Cluster

14 Our Approach is BIRT Analytics 15

15 Also known as Customer Intelligence (CI) 16

16 Customer Intelligence User Experience That s ALL my data in one place! I can do this all by myself! 17 Look what I found! Wow that was fast!

17 Why Customer Intelligence? A Comprehensive Solu/on 18 BIRT Analy/cs is an end- to- end self- service plaeorm for Business Analysts that allows companies to build and effec/ve customer- centric strategy while reducing IT costs: Big Data: Millions to Billions of records at high speed and performance Data Mining for Business Analysts: Diagnos-c Analy-cs and Predic-ons Agility: everything on the fly, no coding, modeling nor pre- processing, users autonomy Out- of- the- box analy/cs for business cases Cost Effec/ve: Low hardware requirements Fully integrated with Selligent

18 Customer Intelligence Graphical Modules that Automate Analy2c Techniques Venn Diagram Set Analysis What group should I review? Discovering Hidden rela-onships Distribu/on Pareto, frequency and distribu2on charts What is the range of distribu-on and its curve? Profile PaAern Detec/on Z- Score paiern match What are common a_ributes? Associa/on Rules Market basket analysis Detect cause and effect pa_erns (milk, diapers & beer) Geographic Profile Where are they? 19 Time Series Forecas/ng Holt- Winters algorithm Predict spending, units, new projects, etc. Decision Tree Predic/on C4.5 decision tree The best product for every customer Clustering and Classifica/on K- Means algorithm Mul-- dimensional cluster

19 Business benefits Eliminate business latencies Autonomous and agile No warehouse lag Business- user easy No IT lag 2me All data Without wai2ng for Hadoop Visual mining No data scien2st lag Predic-ve analy-cs No insight lag Everyone par-cipates No BI lag Creates and accelerates the analy-c cycle No process lag All your data, modeled when you need it, visually mined and segmented, analy-c AND predic-ve. All integrated with your Corporate standards which then opera-onalizes your insights via dashboards, KPIs, interac-ve and ad hoc reports on web or mobile to immediately impact your business. 20 Actuate Corpora-on 2014

20 Leveraging Customer intelligence for your Marke/ng Strategy Covering the common challenges of a customer- centric marke/ng strategy with advanced and easy to use predic/ve analy/cs: Customer Acquisi-on Customer Segmenta-on Customer Reten-on / Loyalty / Churn Next Best Product to recommend Up sell / Cross sell Customer Life-me Value (CLV) 21

21 Challenge 1: Customer Acquisi/on What do my best customers look like? Which prospects are more likely to respond to each campaign? PaAern Detec/on Profile 22

22 Challenge 2: Customer Segmenta/on How do customers group by benefit and poten-al risk? BeAer Classifica/ons & Advanced segmenta/ons Clustering 23

23 Challenge 3: Customer Reten/on What do churners look like? How to predict - and prevent- which customers are likely to abandon me? Churn Predic/on Decision Tree 24

24 Challenge 4: Next Best Product to Recommend What are the customer- product opportuni-es that bring value both to the business and to the customer? Basket Analysis and Product Matrix Associa2on Rules 25

25 Challenge 5: Up- Sell & Cross Selling Opportuni/es What is the best replacement or add- on product for each customer? Can I maximize the customer value by offering them the right product at the right moment through the right channel? Discovering Hidden Rela/onships Venn Diagram 26

26 Challenge 6: Customer Life/me Value What should be the poten-al revenue of each customer? Predic/ng Future Values Time series & Forecas2ng Predict sales, spending, new projects 27

27 Customer Case Study Leading Company in Mul/- sector Loyalty and Direct Marke/ng Division of Loyalty Card Program. Over 6.5 million members which means 43% of Spanish households Over 30 associated companies leading their sectors 12,000 points of sale and 150 websites BIRT Analy-cs for data access and insights Challenges Improve -me- to- market on custoomer communica-ons Ad- hoc complex analysis and segmenta-ons Must interface with 3 rd party applica-ons Perform one- -me analysis in response to specific needs of sponsors IT overload Current deployments Data Warehouse Several BI & Repor;ng tools Requirements Analysis of large volume of data (10 billion records) Disparate data sources Fast deployment and ;me to analysis Internal users: Business analysts Why BIRT Analy;cs Quick data integra;on - All relevant data in one single place Setup & running in days - IT workload reduced End- to- end tool for Marke;ng Analy;cs Easy to use for business users Advanced segmenta;on before, during and aqer the campaign launch Capability to interact, integrate and analyze new data on the fly 28

28 Customer Case Study Leading Company in Telecom Division of Mobile & Internet for Residen/al and Business. +14 millions customers Daily faces +2Tb of data, 14 Databases, 160 tables BIRT Analy-cs for personalized analy-cs and insights Challenges data integra-on is a nightmare Excessive workload in marke-ng campaigns Segmenta-on and analysis through different non- connected tools and apps Need of deep customer insights, not just What- Happened scenarios 29 Actuate Corpora-on 2014 Current deployments Data Warehouse Several Data Marts CRM Requirements Reduce IT workload on data prepara;on for Campaigns Disparate data sources Fast deployment and ;me to analysis Internal users: Marke;ng Intelligence Why BIRT Analy;cs 360º view of customer data through extremely quick data integra;on Shorten campaign process ;me: from days to hours Agile analysis with much bexer insights ready to use in campaigns 20% of improvement in responses

29 The next wave of Customer-centric Marketing Strategies will be powered by personalized insights Are you ready? 30

30 Questions? feel free to ask now or 31

31 Thank you for your aien2on Carlos Álvarez BIRT Analy2cs Sales Representa2ve 32