Chapter 12: Analytics in Action

Transcription

1 Chapter 12: Analytics in Action Disclaimer: All logos, photos, etc. used in this presentation are the property of their respective copyright owners and are used here for educational purposes only Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.1

2 Outline/ Learning Objectives Topic Rapid Pivot Tables Communications Description Learn rapid decision tools, such as Pareto analysis Describe how to create and work with pivot tables Increase communications effectiveness with data Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.2

3 Rapid Decision Models: Pareto Prioritization Name Sales Demographics Geography Psychographics Ale Alpha $1,100 Age 25 Atlanta Aardvark lover Betty Beta $100 Age 44 Boston Bat lover Debbie Delta $300 Age 35 Denver Dog lover Edie Epsilon $200 Age 38 El Paso Egret lover Gary Gamma $1,300 Age 24 Galveston Goose lover Total Sales $3,000 Customer Data, Original Name Sales Demographics Geography Psychographics Gary Gamma $1,300 Age 24 Galveston Goose lover Ale Alpha $1,100 Age 25 Atlanta Aardvark lover Debbie Delta $300 Age 35 Denver Dog lover Edie Epsilon $200 Age 38 El Paso Egret lover Betty Beta $100 Age 44 Boston Bat lover Total Sales $3,000 Customer Data, Sorted by Dependent Variable Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.3

4 Rapid Decision Models: Cross-Sales Model Product B Product A Service C Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.4

5 Cross-Sales Model Name Sales Sales, A Sales, B Sales, C (service) Ale Alpha $1,100 $600 $300 $200 Betty Beta $100 $0 $100 $0 Debbie Delta $300 $0 $300 $0 Edie Epsilon $200 $0 $200 $0 Gary Gamma $1,300 $800 $300 $200 Related Product and Service Sales Data, Original Name Sales Sales, A Sales, B Sales, C (service) Gary Gamma $1,300 $800 $300 $200 Ale Alpha $1,100 $600 $300 $200 Debbie Delta $300 $0 $300 $0 Betty Beta $100 $0 $100 $0 Edie Epsilon $200 $0 $200 $0 Related Product and Service Sales Data, Sorted by Dependent Variable 50% of Product B sales come from cross-sales with A; Service C only sells when customers purchase A and B Top customers consider B and C as essential related products Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.5

6 Supplier Selection Framework PR Agency 1 Company A PR Agency 2 PR Agency 3 Typical scenario: Must select from one of three public relations (PR) agencies Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.6

7 Supplier Selection Framework Selection Criteria PR Agency 1 PR Agency 2 PR Agency 3 Industry Contacts 8: big Rolode 6: out of date 8: big Rolode Social Media Epertise 8: strong focus 5: not a focus 5: not a focus Article Opportunities 5: not a focus 5: not a focus 8: strong focus Award Opportunities 5: not a focus 8: strong focus 5: few awards Crisis Management 8: fast response 3: no focus 5: some focus Cost Structure 1: $$$$$ 3: $$$ 7: $$ Total Scores Scoring: Scale of 1 to 10; 1 = Poor; 10 = Outstanding Straight Sum: Add scores to find total; Highest score gets selected Modified Sum: Disqualify supplier if they fail any one category Weighted Sum: Adjust significance of certain criteria Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.7

8 Metrics in Marketing Campaigns Sample Bold Metrics Potential Campaigns 33 Million: Americans living alone Campaigns for single-serving meals 70% of people 12 and older who abuse Campaigns with anti-drug message prescription drugs say they get them from a friend or relative 49%: Dog napping increase: Campaigns for dog security 53%: Percentage of overweight dogs Campaigns for diet dog food 13.9 hours/week: Time spent on tablets Campaigns for tablet apps 61%: Non-essential s delivered Campaigns for spam filters 3 Billion/mo: Hours of YouTube watched Campaigns to promote video usage Sample Bold Metrics and Campaigns Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.8

9 Metrics in Marketing Campaigns 80% of People over Age 45 Consider Changing Careers But Only 6% Actually Do Eample of Jutaposition Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.9

10 Pivot Tables Name Sales Date of Sale Product Channel Ale Alpha $1,100 January Product A Store Betty Beta $100 February Product B Internet Debbie Delta $300 February Product B Store Edie Epsilon $200 January Product B Internet Gary Gamma $1,300 January Product A Store Original Data Set Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.10

11 Pivot Tables Create Pivot Table Ecel Home Insert Choose the data set to analyze Select a table or range: Table Range: Sheet1:$A$1:$E$6 Use an eternal data source Pivot Table A B C D E F G Choose where you want the Pivot Table report New Worksheet Eisting Worksheet OK Launching Pivot Table in Ecel Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.11

12 Pivot Tables Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Column Labels Row Labels Values Ecel s Pivot Table Field List, Based on Original Input Data Set; Select Sales and Product to get basic table of sales by product Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.12

13 Pivot Tables A B C D Row Labels Product A Product B Grand Total Sum of Sales Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Row Labels Product Column Labels Values Sum of Sales Pivot Tables: Basic Report: Sales by Product; Select Date to see how sales vary over time Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.13

14 Pivot Table A B C D Row Labels Product A January Product B January February Grand Total Sum of Sales Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Row Labels Product Date Column Labels Values Sum of Sales Pivot Tables: Sales by Product and Date Select Channel to see how sales vary with type of Distribution Channel (store) Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.14

15 Pivot Table Row Labels Product A January A B C D Retail Store Product B January Internet February Internet Sum of Sales Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Column Labels Retail Store 300 Row Labels Values Grand Total 3000 Product Sum of Sales Pivot Tables: Sales by Product, Date, and Channel (Added Date, and then Channel) What if we had added Channel, and then Date? Stephan Sorger Marketing Analytics:Analytics in Action:Ch Date

16 Pivot Table Row Labels Product A A B C D Retail Store January Product B Internet January February Retail Store Sum of Sales Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Column Labels February 300 Row Labels Values Grand Total 3000 Product Sum of Sales Pivot Tables: Sales by Product, Date, and Channel (Added Channel, and then Date) Date Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.16

17 Pivot Table Row Labels Product A January Product B January February Grand Total A B C D Sum of Sales Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Row Labels Product Date Add to Report Filter Column Labels Values Sum of Sales Adding Field to Report Filter Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.17

18 Pivot Table Channel (All) Internet Retail Store A B C D (All) OK Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Channel Row Labels Product Date Column Labels Values Sum of Sales Selecting Reports using Report Filter Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.18

19 Pivot Table A B C D 1 Sum of Sales Column Labels 2 Row Labels Internet Retail Store Grand Total Product A January Product B January February Grand Total Pivot Table Field List Choose fields to add to report: Customer Sales Date Product Channel Drag fields between areas below: Report Filter Row Labels Product Date Column Labels Channel Values Sum of Sales Pivoting Pivot Tables: Transposing from Columns to Rows Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.19

20 Chart Selection B A $500K $400K $300K A B C C D E $200K $100K Revenue 0 D E Sales Revenue by Product Sales Revenue by Product Pie Chart Vertical Bar Chart Typical Applications: -Market share breakdown -Revenue breakdown -Marketing budget breakdown Typical Applications: -Sales revenue comparisons -Before-After comparisons -Competitive comparisons Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.20

21 Chart Selection $1,000K $800K $600K $400K A $200K C D Revenue E 0 Sales Revenue by Product $1,000K $800K $600K $400K $200K Revenue 0 C A E D Sales Revenue by Product 100% C E 80% 60% 40% A D 20% 0 Sales Revenue Contribution Clustered Column Chart Stacked Column Chart 100% Stacked Column Chart Column chart variations available in Ecel Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.21

22 Chart Selection 0 $100K $200K $300K $400K $500K B A C D E Revenue Horizontal Bar Chart Typical Applications: -Long category names -Tornado charts (see net slide) Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.22

23 Chart Selection Male Female Age 50-up Age Age Age Age Displays population comparisons Requires data preparation (see table) Male Population, X Tornado Chart Female Population, X 1000 Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.23

24 Chart Selection $7K $6K $5K $4K A A Product B Overtaking Product A $3K $2K B B $1K 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Clustered Vertical Bar Chart Line Chart Typical Applications: -Trends comparing internal data with other internal data -Trends comparing internal data with eternal data Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.24

25 Chart Selection A1 A2 B2 C2 C1 B1 Scatter Chart Doughnut Chart Radar/ Spider Chart CAUTION: Use sparingly in front of general audiences Can be confusing, with large chance of mis-interpretation Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.25

26 Chart Enhancements Sales increased from $4.2 M in 2012 to $5.3 M in 2013 Words and Numbers Sales Product 1 $3.0M $4.0M Product 2 $1.2M $1.3M Total $4.2M $5.3M Data Table Sales: Product 1 Basic Chart Sales up 30% Sales up 30% Sales up 30% $3.0 M in Sales Sales: Product 1 Sales: Product 1 Chart with Headline Chart with Trend Arrow Sales: Product 1 Chart with Threshold Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.26

27 Chart Enhancements Sales by Product Product 1 Product 2 Sales by Channel Channel 1 Channel 2 Breakdown: Products Breakdown: Channels Product 1 Actual Forecast Product 1 Acme Brand Competitors Comparison: Forecast Comparison: Competition Comparisons using lines of different types Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.27

28 Chart Enhancements $8M $7M $6M $5M 20% Sales Growth in 2013 $5M Threshold $4M $3M $2M $1M 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Addition of Trend Arrow, Threshold, and Headline Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.28

29 Marketing Analytics Ethics Yes No Results of Survey: Would you recommend Acme products to others? Yes No Truncating Trickery The Ethical Way With great power comes great responsibility Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.29

30 Data-Driven Presentations Engineering Department Status Engineering resources are very low; definitely need more engineers Some engineers working many hours per week Engineers risk getting burned out from working so many hours New projects coming up will require more resources than we have Engineering resource types Engineering resource type A: have 10 engineers; need at least 12 Engineering resource type B: have 3 engineers; need at least 4 Engineering resource type C: have 5 engineers; need at least 6 Engineering resource type D: have 15 engineers; need at least 20 Possible slips to schedule can occur unless we hire more engineers Recommend hiring at least 2 additional engineers in net month Many engineers complaining to their management about workload The wrong way to present to eecutives -Not relevant to CEO s KPIs -Not likely to result in intended consequence (hiring more people) Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.30

31 Analytics into Action Professional Services Organization Department Status Will Stop Producing Incremental Revenue Here Current Resource Level Department Revenue and Resources Projected Revenue Revenue to Date Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec The right way to present to eecutives -Relevant to CEO KPIs -Outcome-focused, instead of process-focused Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.31

32 Check for Understanding Topic Rapid Pivot Tables Communications Description Learn rapid decision tools, such as Pareto analysis Describe how to create and work with pivot tables Increase communications effectiveness with data Stephan Sorger Marketing Analytics:Analytics in Action:Ch.12.32