Effectively Measuring Social Media
Social media marketing spend is the fastest growing investment, and will pass email marketing in 2013.
Facebook and Twitter command huge and growing audiences, and are a proven way for brands to reach their customers.
40% of Facebook users “like” companies
51% of twitter users follow companies, brands and products
Social likes and tweets are really just another form of a review.
Do social channels provide any incremental value?
- Social sites are second only to display for generating new visitors.
- Facebook engenders more session loyalty than email, twitter or referring sites.
- Facebook referrals are more efficient at conversions
Why build a social following?
People spend 90% of their Facebook time in their news feed. You NEED to be in the feed. Engagement makes the message viral. Once engaged, that customer is now an evangelist to an average of 137 like-minded friends. So, create a fun and engaging social content and contests. Don’t just throw offers at them.
Tracking Earned Media:
What’s Hot? Tools are needed to show where to focus on good content and good audiences. What’s converting? Once you track it, you need to appropriately attribute earned media alongside all channels. So, track the social channel, then compare it to other channels.
Challenges of Social Data Measurement
- Multiple, shifting sources (which leads to)
- Inconsistent dataset
- New behaviors = new data types (what does it mean when someone likes…)
- Inconsistent quality
- No measurement standards (biggest issue)
- Privacy considerations
Social Measurement Sand Traps (3 Challenges)
- Engagement – no agreement on what it means. Decide what it means for you and be transparent with your organization on that.
- Reach – Partial datasets, inconsistent measures
- Sentiment – Alogrithmic sentiment ~ 75% accurate at best
- Influence – Not all influence is created equal. Someone may have be an influencer to you for web tools, but not for cars or makeup.
Have to include new tools that specialize in social space, and old tools that specialize in enterprise crm, analytics, market research, so need tools that are a blend of both.
Each corporate department looking at data in very different ways.
All this adds up to…
data challenges + tool challenges + organizational challenges =
Before you do anything else, have a goal for measurement!
Use approriate metrics at each level:
- Social strategist: engagement metrics: fans, followers, clicks
- Line Of Business/Geo Stakeholders: social media analytics, insights, share of voice, word-of-mouth, resonance
- Corporate Level – Business metrics: revenue, reputation
The Elephant in the Room: ROI of social media (which may be the wrong question)
ROI = [Gain from investment – cost of investment] / Cost of investment
A better question might be: What is the BUSINESS VALUE of social media?
Case Study: Let’s imagine a Comcast customer tweets a complaint about not getting a particular TV channel in his area.
Think KPI, not [just] ROI when looking at this tweet.
How do each of the departments look at this tweet?
- Brand Marketing – Brand impact? Do we deal with it, ignore it, or what?
- Product Marketing – Isolated incident or trend? Should we offer it?
- Competitive Intel – Vulnerability or opportunity to outshine competition?
- Operations – How much did it cost to resolve?
- Customer Service – Did we make the customer happy?
Six Use Cases for Social Media Value
- Brand Health – Understand how people talk about your brand on social web.
- Marketing Optimization – Decision support for social marketing investment
- Revenue Generation – Generating leads, conversions, and revenue via social media
- Operational Productivity – Reducing operational costs via social media (saving money in call centers, for example)
- Customer Experience – Helping customers and improving their experience with your company and across channels
- Product Innovation – Consumer-led ideation
Social Insights and KPIs
1. Brand Health
- What topics spark conversation?
- What topics spark emotion?
- Sentiment by social media channel
- Stated intent to purchase
- Whether brand gets credit for promotions
- Volume of social media mentions
- Share of voice vs. competitors
- Number of fans/followers
- Highest-performing topics
- Number of brand mentions per campaign
2. Marketing Optimization
- Which channels generate highest visit loyalty
- Which platforms generate highest logyalty/conversion/revenue
- Where conversations about your brand occur online
- Likeliness to buy based on specified behaviors
- If social channels cannibalize other online channels
- Most effective times to post social content/engage
- Where to find brand advocates
- Conversions/sales by channel
- Impressions by channel
- View-through/click-through by channel
- Visitor loyalty
- Advertising equivalent of earned social media
- Most followed account/people who talk about your brand
3. Revenue Generation
- Effectiveness of social channels for conversion and revenue generation
- Likeliness to buy
- Impact of social media on search results
- Whether social channels are cannibalizing other channels
- Conversions by channel
- Sales by channel
- Visit loyalty
- Improved search engine placement
4. Operations Productivity
- Potential cost savings from deflected calls
- Most active adovocates
- Which services issues best answered online
- Knowledge base gaps
- Number of calls deflected
- Call deflection savings
- Number of advocates
- Value of advocates
- Reduction/deferred hiring of FTE
5. Customer Experience
- Most common service and product issues
- Triangulation of above with service channels
- Acceleration of issues
- Sentiment and emotion drivers
- Number of customer service issues addressed via social channels
- Percentage escalated and resolved
- Percentage of positive ratings and reviews
- Sentiment ratios
- Most common service and product issues
- Customer requests
- Competitive opportunities and threats
- Speed to market
- Product development efficiency
The Future of social Analytics:
- Enterprise-class capabilities such as data quality, integration, governance and scalability will be checkbox items
- A basic ability to understand social data will be come a critical skillset
- Machine learning will continue to improve, but probably not as fast as everyone wants it to.
- In the next 1-2 years, we’ll see social benchmarks
- Ultimately, the terms “social media”, “social business” and “social analytics” will go away.
Focus on which is incidental and which is vital.
- Have an objective
- Know your data
- Think globally, not locally (across the company departments)
- Think directionally (look at data patterns over time)
- Don’t underestimate the soft stuff (processes and people)