This weekend, a newly hired marketing manager asked my opinion on social media analytics. His company is medium sized construction company and had recently ventured into housing business. As I spoke to him and advised on social media analytics strategy, I thought of documenting the gist of what I said in this blog.
Today, every company in fortune-500 list is using an array of social media analytics - from a host of data analytics services companies. Even smaller companies with revenues in less than $10M are now buying social media analytics.
Social media companies are also making it easier for companies to collect data through APIs & its free. Facebook insights, twitter analytics, Google analytics etc. are so easy to use - that even small start ups can benefit from it.
So this raises a question: Is the custom built sophisticated big data analytics any better than the free versions from Facebook, Twitter & other social media?
At the first level, paid analytics looks more sophisticated and definitely looks good. Vendors offer pretty reports and better interfaces. For a higher price, few companies offer better math that is used to quantify ambiguous metrics - such as depth of customer engagement or Potential reach of the product.
A common justification for paying for social media analytics is usually:
"Customers are very important to us, so why not spend some percentage of marketing spend to know & understand what customers are saying."
"Hearing what customers are talking - will help us better position out advertisements. Even a 1% increase in customer response to an advertisement leads to 10-15% increase in sales."
While there is no denying that there is value in social media analytics, businesses must spend considerable time to conduct rigorous data modeling ahead of time to ensure that the metrics provided by a third-party analytics program/services are meaningful to the business. Without an upfront data modeling - you will end up with a flood of data and reports - that does not tell anything new.
Data modeling starts with identifying the right data - Not just data. You need to filter out spambots, auto retweets and clickbots etc.. Next, you need to identify keywords or phrases that are relevant to your business. For example word "suck" is generally bad for retail, but a good word for vacuum cleaners. It takes time to identify which phrases are "positive," "neutral" or "negative".
Keyword based analytics can give huge value - but only when it is done right. Businesses need to spend time/effort to identify keywords & refine keywords on periodic basis.
Once data modeling is done, the next is to firm up on the strategy:
- How to deal with the information you are getting from social media feeds?
- How to manage customer complaints?
- How to increase traffic with social media?
In the world of social media, the time to respond to customer complaints and negative comments is really short. So businesses needs to have a response strategy in place - before starting off on social media analytics.
Closing Thoughts
Unless businesses have done their homework in terms of data models, response strategy, It is best to use the free basic metrics provided by the social media platforms. Only when you have a strategy - then invest in social media analytics.
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