Whitevector blog

Whitevector’s industry is usually referred to as Social Media Monitoring, but increasingly also the words ‘analysis’ and ‘analytics’ are associated with what we do. With this post we want to elaborate how social media analysis can be used in a more analytical way and also combined with common web analytics, such as Google Analytics.

The main objective for common web analytics is to understand volume of visitors, behaviour of visitors on the site and traffic sources of the visitors. Meanwhile the goal of social media analytics is to turn the mass of social media comments into quantitative statistics measuring brand visibility in product contexts, lead generation potential, consumer preferences and analysing influential social media sites and profiles. This is the first part of the posting, and we will follow up with a posting that includes practical examples so that the basic idea will not remain too abstract.

Social media monitoring is often perceived as following postings or tweets about brand mentions without focus on context and only understanding ‘what is being said about us?’ While this is very useful and social media analysis always starts from the basic monitoring, we could argue that the most valuable use cases of social media analysis include a clear analytical approach where the context of the numbers is understood, social media analysis is combined with other metrics and KPI’s are set.

So how are the numbers put into context? In the first place, there are three basic ways:

• Benchmarking against competition
• Comparing changes over time
• Setting target values to visibility metrics

Competitor benchmarking is best done with direct comparisons in the respective category or benchmarking the brand against category average. Changes over time are best understood through weekly or monthly changes and through plotting for example six months of data into the chart to understand the trend. Third part, setting target values (or KPI’s) and benchmarking measurement results to the objectives is a simple but efficient way to understand social media activity as part of the digital marketing performance.

These ways to present social media data in context are all basic approaches in social media analysis, but our experience shows that too often social media monitoring is left outside the analytics functions even when the client already has an appropriate service in place and the data is there.

The next step is to generate insights by combining social media analytics with other metrics. Thanks to our Facebook followers we found a good example on how web analytics and social media analytics can be combined to determine social media campaign effect. Social Times published a posting last February that is headlined The 10 Social Media Metrics Your Company Should Monitor. The article introduces a list of metrics that measure social media campaigns to understand success and ROI, and the metrics are based basically on both common web analytics and social media analytics.

Social Times argues that in order to determine ROI from social media campaigns looking only at visitors, sources of traffic, network size and the quantity of commentary about a brand or product is not enough, and introduces an extended set of metrics. The set consists of social media leads, engagement duration, bounce rate, membership increase and active network size, activity ratio, conversions, brand mentions in social media, loyalty, virality and blog interaction metrics. Of these ten the last four are derived from social media analytics whereas the first six are more based on web analytics.

This set is a good example of a toolkit that answers something that web analytics or social media analytics alone cannot extend to. For example, a company website might see a peak in visitor traffic, even though there have not been any recent ad campaigns. While web analytics shows the change in traffic, social media analytics can help to find answers to what is the reason behind a sudden traffic increase. Furthermore, understanding the reasons behind the traffic enables to make the most out of the opportunity and improve the performance of your site further.

Social media content is a significant driver of web traffic, which makes it natural to combine the data. Social media analysis helps to determine the drivers for the traffic offering information and a qualitative view on what happens before the visitor ends up on a landing page. This extends the visibility of an online lead generation funnel for site owners. This also shows a difference to web analytics: social media analysis is a combination of both numbers and qualitative insights.

And thanks to the Social Times people for a good post!