Saturday, January 26, 2013

Metrics for Social Analytics

Due to the complexity of the structure and conversations going on the social networks, it's important to note the uniqueness of social analytics against web analytics in general sense.

1. What's the difference between social analytics and web analytics in general? What are the metrics usually used in the latter?

Generally speaking, web analytics can reflect the whole business process from product promotion to sales completion, whereas social analytics are more focused on the tunnel through which the product is propagated and customer acceptance.
According to Web Analytics 2.0, a metric is quantitative measurement of statistics describing events or trends on a website. However, as suggested by Paul. G Strupp, two types of metrics are commonly used in web analytics, one is MTC (Measure to Control), and the other is MTA (Measure to Analyze). The former is usually quantitative measurement providing answers to questions like "How many...?" " How much...?" "How often...?", while the latter could be both quantitative and qualitative that answers questions like "Why...?" "Who...?" "Where...?" "How are users...?"

Since the approach of web analytics has progressed into "outcome-based" era, the metrics adopted for each individual analysis case are very largely dependent on the objectives of the organization or individual that the analysis is serving. Below is some examples of objective-oriented metrics selection,
  • Conversation Rate or Revenue Trends for eCommerce websites like Amazon.
  • Depth of Visit for websites like Wonkblog.
  • Visitor loyalty for websites like Facebook.
However, as diverse as the selections of metrics might be, web analytics in general serve the goal of discovering visitor browsing and purchasing behaviors. Being a very trendy part of this topic, social analytics place more emphasis on the effectiveness of the online propagation of certain product or brand, as well as the customer perspectives towards them.

2. Metrics chosen in social analytics

Each metric chosen is tightly associated with certain KPI. Differentiated by complexity of deriving from raw data and ease of interpreting into business sense, each KPI can be reflected by several basic metrics as well as advanced ones. 
Let's say your company is in industry IND, and you trying to promote or track you product PRO online. we'll see how it works on the platforms of social networks, and which metrics we want to look at.
Basic Metric: SOV ( Figure 1.1)

Figure 1.1
Number of Conversations mentioning your product or brand out of the total number of industry conversations.
Advanced Metric:  SOV (Figure 1.2)
Figure 1.2

Number of brand or product mentions by influencers & vocal customers out of total number of relevant mentions.
Basic Metrics: 
Social Reach: total # of followers across all social platforms (Figure 2.1)
Figure 2.1
Growth: Month-over-Month or Quarter-over-Quarter
Engagement = (likes+ shares+ retweets+ blog comments)/(# of published posts of pieces of comment) (Figure 2.2)
Figure 2.2
Advanced Metrics:
Engagement: by campaign; per specific social platform; per specific post.
Influencer Engagement = # of influencers aware of brand out of total # of industry influencer (Figure 2.3)
Figure 2.3

Cost/ Benefit Analysis = ROI of special campaigns/ ROI of traditional marketing campaign
Basic Metric: Lead Generation Effectiveness (Figure 3.1)
Figure 3.1
Number of new leads from social channels out of number of total leads 

Advanced Metric: 
Lead Generation Effectiveness: Number of leads generated or influenced by social campaign out of number of total leads
Basic Metrics:
Social Sales Effectiveness = # of sales coming from social channels out of total sales;
Growth In Sales From Social Channels: Month-over-Month; Quarter-over-Quarter; Year-over-Year.

Advanced Metrics:
Repeat Purchases = # of customers buying more due to social engagement out of # of purchase

Overall Sales Effectiveness: Growth in average deal size; shorter sales cycles; more deals per sales person due to deeper customer insight
Basic Metric: Complaint Visibility/ Feedback (Figure 4.1)
Figure 4.1
Ability of customer service reps to post or comment on brands social channels
Advanced Metric: Social Comment Integration (Figure 4.2)
Figure 4.2
Ability to integrate social customer data & communication into voice of customer applications;
Proactive issue escalation (mining of social posts from customers to identify customer service issues or defection triggers);
Text & Sentiment analysis of social posts of customers.

Kaushik, Avinash. Web Analytics 2.0. Indiana: Wiley Pubulishing, Inc., 2010.
Actionable Social Analytics: From Social Media Metrics To Business Insight. April, 2012.

1 comment:

  1. I find social analytics very interesting. First from the perspective of challenge. It's very difficult to tie KPI's directly to KBR's. How much does 500 facebook likes affect revenue growth? And also from the perspective of the fact, that for the first time companies have the ability to monitor word of mouth advertising. The KPI's you described where great. But I do think it is tough to tie them directly to sale or profit. I think it would be interesting to simply tie social analytics and basic data mining together and see correlations between social media KPI's and revenue growth, profitability, etc. From a bigger picture sense, it may be a practice that puts more weight behind things like the net promoter score.