DATA ANALYTICS MICHELLE LELEMPSIS, CAUSEIS TRAIN

Transcription

1 DATA ANALYTICS MICHELLE LELEMPSIS, CAUSEIS TRAIN + LEARN NETWORK +

2 DATA ANALYTICS Why Data Analytics and Reporting Strategies? The 7 Cs of Data Analysis What questions should you be asking your data? Case study: Profile, Engagement, Retention Reporting

3 INTRODUCTION Michelle Lelempsis Solutions Consultant at causeis Who am I? Worked with imis for over 10 years Data Analyst by default! Help organisations drive decisions through data driven evidence Helped organisations increase retention, improve efficiency through data analytics

4 HOW DO YOU MANAGE YOUR DATA ANALYTICS

5 HOW DO YOU MANAGE YOUR DATA ANALYTICS You re using this method if you hear these sorts of statements Our biggest loss of members is from the aging database Membership managers make statements about their members but they don t access reports All members receive the same renewal communication We ve always done this process Executive KPIs are not tied to metrics e.g. We re committed to growing membership.

6 HOW DO YOU MANAGE YOUR DATA ANALYTICS

7 HOW DO YOU MANAGE YOUR DATA ANALYTICS You re using this method if you hear these sorts of statements Our biggest loss of members is from the aging database as 40% of members are over 60 and the average age is increasing yearly Membership managers and Executive review key membership statistics that are segmented and targeted Membership renewals are targeted and segmented by influencers Processes are constantly evolving and being reviewed Executive KPIs are tied to metrics e.g We will grow membership by 2% in the first quarter. We will decrease our time to process a renewal or donation by 30% over the next year.

8 INTRODUCTION Where are you on your Data Analytics journey? We don t analyse our data Operation Reports Strategic reports Engagement reporting Predictive reporting Data visualisation

9 CHRIS RIDDELL Welcome to our Future

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11 WHY DATA ANALYTICS? ASI 2015 Benchmarking Report GREATEST CHALLENGE inadequate tools to generate the reporting and analysis they need to make sound business decisions. HIGHEST PRIORITY they feel they must have access to better intelligence on their members and be able to report on and analyse critical data.

12 WHY DATA ANALYTICS? Gaps in the ASI 2015 Benchmarking Report 7% did not know their current retention rate 21% did not know their change in retention rate 32% did not know their overall member engagement rate 25% did not know their market saturation rates Who is measuring all of these key association analytics?

13 WHY DATA ANALYTICS? According to Gartner the top CIO priority for 2015 is Business Intelligence and Data Analytics "The power of data will unlock possibilities for you, your business and customers. Chris Riddell

14 Framework for Data Analysis

15 THE 7 C S OF DATA ANALYTICS Data Analytics does not have to be complex Data Analytics is not about organisational data warehouse or expensive software The 7 C s provides a framework for embarking on Data Analytics

16 WEB RESOURCES AND READING LIST The Accidental Analyst: Show Your Data Who's Boss Eileen McDaniel & Stephen McDaniel

17 THE 7 C S OF DATA ANALYTICS Questions Data Analysis Results 1. Choose 2. Collect 3. Check 4. Clean 5. Chart 6. Custom 7. Communicate

18 THE 7 C S OF DATA ANALYTICS 1. Choose your Questions: The single most important step in analysis is to chose the questions that you re organisation is trying to answer. 2. Collect your data: First you have to collect the right data for your question and organise it one place. 3. Check out your data: This C demonstrates how to become knowledgeable about your data set. 4. Clean up your data: No data is perfect, but there are a few tools you can use to clean your data. 5. Chart your analysis: Which charts are most useful for presenting company data. 6. Customise your analysis: Specific data requirements sometimes require custom charts and data analytics. 7. Communicate your results: What is the best way to communicate organisational results?

19 How to ask a Question

20 CHOOSE YOUR QUESTIONS The quality of an answer depends on the quality of the question.

21 CHOOSE YOUR QUESTIONS It is considered the most important C as it guides the entire analysis phase. Take your time on this phase to ensure that you don t waste time later in the reporting. How do find the right questions? Is it a problem we are trying solve? What will the analysis be used for? Who are the stakeholders? Is the analysis for strategic, operational or analytical purposes? Case Study: Why is our membership not growing?

22 CHOOSE YOUR QUESTIONS Gather information on the question: Learn from the past ask other staff about the question or problem, what did they do in the past? Review any past reports What has been implemented previously? Involve others Meet with other staff on the issue or question Involve others to ensure the success of the outcomes You are more likely to succeed when involving key areas Case Study: Key stakeholders Membership, Communications and Executive

23 CHOOSE YOUR QUESTIONS Do not limit your analysis Develop your questions without any data limitations It is easy to limit our questions due to lack of data or your typical internal data reporting Expand questions as though you are not limited to data External data is often easily accessible Any limitations that are discovered through the remaining phases can be reported on in the outcomes which may drive improvements in data capture Case Study: Do we know our market share? How would we find this? Who are our members? How many renew and what is our retention rate?

24 CHOOSE YOUR QUESTIONS So what questions could we ask in response to Why is our membership or donor base not growing?

25 CASE STUDY: LIST OF QUESTIONS MEMBERSHIP What is the retention of membership? What is the retention of members by category? What is the retention of members by segment/payment type? What is the retention of members by demographics? What is our retention compared to other associations? Where are new members being acquired from? Who is resigning? What category, segment or demographic?

26 CASE STUDY: LIST OF QUESTIONS FOR FUNDRAISERS What is the retention of our donors? How many are new donors (first gift in last 6 months)? How many are active donors (donated in last 6 months)? How many are current donors (donated in last 12 to 18 months)? How many are lapsed donors (donated in last 18 to 24 months)? How many are very lapsed donors (donated in 24 to 48 months)? Average gift by payment type Average number of gifts per donor Average duration between giving

27 HOW CAN UNDERSTAND OUR CUSTOMERS? imis and other data sources imis reporting tools iqa, SSRS, Crystal reports, SQL, other reporting tools that can interface Data Analytics software YellowFin, Tableau

28 WHAT AREAS CAN WE REPORT ON 1. Profiling - Who are our customers? Segments, groups, profiles 2. Engagement - What are they doing? Engagement reporting? What are these segments participating in? 3. Retention - What is their retention? Can we identify influencers on retention?

29 PROFILE REPORTING Let s do a quick example of a basic member profile with iqa (or a sneaky SQL query) and Excel for pivot functionality (why?) Members by age, gender and years of membership What data do we need to do this? Where is the data? What other reports could do?

30 ENGAGEMENT REPORTING Which members or donors are using which services?

31 ENGAGEMENT REPORTING Work with your membership, fundraising teams to identify what are your key services and benefits Are they tracked in imis? Where is the data stored? Is it meaningful i.e date driven, coded and control Don t pick all of your services but pick say 5 or so.

32 HOW CAN I UNDERSTAND OUR CUSTOMERS Let s have a go at building a report on Engagement of Members by Open Rates of s over 12 months What else could we report on?

33 HOW CAN I UNDERSTAND OUR CUSTOMERS Yes! You can add these to your imis Staff Site

34 HOW CAN I UNDERSTAND WHAT OUR CUSTOMERS ARE DOING?

35 HOW CAN I UNDERSTAND WHAT OUR CUSTOMERS ARE DOING?

36 RETENTION REPORTING Which members are being retained? What are your retention influencers?

37 RETENTION REPORTING How can you simplify retention reporting? Retention Rate = Renewed Members / Total Members Offered E.g 90 members renewed out of 100 = 90% What is a good retention rate?

38 RETENTION REPORTING Charities have an activity that they use to track Appeals via the REQUEST

39 RETENTION REPORTING So why don t we use this methodology for Renewals?

40 RETENTION REPORTING So why don t we use this methodology for Renewals?

41 RETENTION REPORTING So why don t we use this methodology for Renewals?

42 RETENTION REPORTING

43 RETENTION REPORTING

44 RETENTION REPORTING Report against all segments, factors to identify influencers Profile (new vs old) Engagement Retention

45 RETENTION REPORTING Highlight opportunities e.g new members had a 75% retention whereas the total membership retention was 90% Engagement drives retention 30% higher retention for event attendees, 5% higher retention for those that open and click through an Automatic payers vs annual payers So what can be done?

46 RETENTION REPORTING Modify business processes to communicate / segment / target Use these retention segments as predicative analysis

47 RETENTION REPORTING Modify business processes to communicate / segment / target Use these retention segments as predicative analysis Identify your retention influencers Payment method (Annual vs Automatic) New or Existing Members Category

48 RETENTION REPORTING Modify business processes to communicate / segment / target Use these retention segments as predicative analysis Identify your retention influencers Payment method (Annual vs Automatic) New or Existing Members Category

49 RETENTION REPORTING Let s have a look at predictive revenue report for budgeting via retention influencers

50 BUT HOW DO YOU KNOW IF YOU RE DOING WELL? Marketing General Informz benchmarking reports

51 BUT HOW DO YOU KNOW IF YOU RE DOING WELL?

52 BUT HOW DO YOU KNOW IF YOU RE DOING WELL?

53 DATA ANALYTICS IN THE FUTURE

54 DATA ANALYTICS IN THE FUTURE GOVERNANCE AND SELF-SERVICE ANALYTICS BECOME BEST FRIENDS VISUAL ANALYTICS BECOMES A COMMON LANGUAGE DATA INTEGRATION GETS EXCITING ADVANCED ANALYTICS IS NO LONGER JUST FOR ANALYSTS. PEOPLE BEGIN TO DIG INTO DATA.

55 WEB RESOURCES AND READING LIST The Accidental Analyst: Show Your Data Who's Boss Paperback by Eileen McDaniel & Stephen McDaniel 2015 Global Benchmark Report Membership Performance by Advanced Solutions International Marketing General, Inc. - Leaders in Membership Marketing at Informz Benchmarking reports at Chris Riddell, Futurist and Technologist Reporter at

56 QUESTIONS Questions? Michelle Lelempsis Solutions Consultant Causeis Mobile:

57 WITH THANKS TO OUR SPONSORS NIUG DISCOVERY CONFERENCE TRAIN + LEARN NETWORK +