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Cost Deflection Case Study
Mission:

Improve customer experience of Microsoft Office Live Support
Community and decrease cost of product support

Strategy:

• Develop an interoperable community platform that consolidates existing
content repositories into a single portal.

ComBlu’s
Role:

• Integrate “spaghetti bowl” of support and product sites into single gateway for content and
conversation
• Activate customer advocates as product mentors and a word-of-mouth engine
• Drive preference and stimulate product subscriptions

Results:

• Decreased cost of support by > 60%
• Exceeded community answer rate (Goal: 50%;
Actual: 77%)
• Increased support page views by 77% for
Office Live Small Business and 359% for Office
Live Workspace

2
Case Study: Microsoft Office Live
Support Costs
per Minute
$0.70
$0.60
$0.50
$0.40

$0.68
$0.56

$0.30

$0.20

$0.24
$0.10
$0.00

Telephone

Email
3

Community
Case Study: Microsoft Office Live

What
happened
to cause
this drop?

4
Case Study: Microsoft Office Live

• Support agents failed to answer questions.
• The root cause turned out to be a technical problem that prevented agents from
responding to forum posts.

5
Microsoft Office Live Results: Exceeding Expectations

Office Live Small Business
Support Page View Increase Post ICSE:

Office Live Workspace
Support Page View Increase Post ICSE:

77%

359%

Percentage of Active Users Who Regularly Use the Community:

34%
Community Answer Rate Goal:

Actual Community Answer Rate:

50%

76.5%

Decrease in Per-incident Hard Dollar Customer Support Costs:

283%

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ComBlu Cost Deflection

  • 2. Mission: Improve customer experience of Microsoft Office Live Support Community and decrease cost of product support Strategy: • Develop an interoperable community platform that consolidates existing content repositories into a single portal. ComBlu’s Role: • Integrate “spaghetti bowl” of support and product sites into single gateway for content and conversation • Activate customer advocates as product mentors and a word-of-mouth engine • Drive preference and stimulate product subscriptions Results: • Decreased cost of support by > 60% • Exceeded community answer rate (Goal: 50%; Actual: 77%) • Increased support page views by 77% for Office Live Small Business and 359% for Office Live Workspace 2
  • 3. Case Study: Microsoft Office Live Support Costs per Minute $0.70 $0.60 $0.50 $0.40 $0.68 $0.56 $0.30 $0.20 $0.24 $0.10 $0.00 Telephone Email 3 Community
  • 4. Case Study: Microsoft Office Live What happened to cause this drop? 4
  • 5. Case Study: Microsoft Office Live • Support agents failed to answer questions. • The root cause turned out to be a technical problem that prevented agents from responding to forum posts. 5
  • 6. Microsoft Office Live Results: Exceeding Expectations Office Live Small Business Support Page View Increase Post ICSE: Office Live Workspace Support Page View Increase Post ICSE: 77% 359% Percentage of Active Users Who Regularly Use the Community: 34% Community Answer Rate Goal: Actual Community Answer Rate: 50% 76.5% Decrease in Per-incident Hard Dollar Customer Support Costs: 283%

Notas del editor

  1. The traditional product support model heavily relied on phone and email support, which had the highest cost structure. The goal was to flip the model on its head and move the majority of support to the community model, which would use brand advocates as the primary peer mentors in answering questions and helping other customers with product questions and challenges. In addition, MSFT wanted to reassign people from the call and email centers to be part of the advocate corps in the community.
  2. The overall KPI was to decrease the overall cost of support. These KPIs are indicators of the vitality of the community model. Other metrics included: number of calls, number of email, numbers of FTEs dedicated to call and email, etc.So again, we have a point in time when we fell off the cliff here.
  3. The role of the agents is to jump in if the community fails to answer a question within a specific time period. Then, an alert system notifies the agents that they need to jump in and respond inside the community. The tracking allowed us to surface a tech problem with the alert system that, once fixed, turned performance around.