Brands have realized social media has become an integral part of business strategies. The data from social networks is similar to any other form data collected by your company- but the data collection process is often disorganized and usually comes from vastly different channels. However, forward thinking companies see social networks as a significant data source for informing business intelligence.
The reasoning is clear. By collecting and analyzing social media data alongside traditional corporate BI, companies have a better understanding of who their consumers are and how they are discussing the brand and its products and services. With social data, brands can more effectively develop insights and answering practical questions about product sales performance and feedback in granulated geographic regions. Social data can explain why a product is selling so well in US, for example, and can help detect early trends that drive product development or the effective messaging to market them. Business Intelligence will help in the visually representing this data so that it becomes easier to identify new trends.
The lack of connection between social data and other data sets can contribute to:
- An incomplete understanding of the factor affecting your business
- Manual or siloed searches across different systems
- Duplication of data processes resulting in redundant practices
- An inferior understanding of customers and prospects – mapping consumer interactions with social data and CRM records helps companies put customer insights into the context of existing customer relationships
Why should your business integrate social data into its business intelligence strategies?
With the aid of appropriate listening tools, your brand will have access to additional insight which traditional BI datasets are often lacking. For example, the interactions consumers have on social networks give you immediate access to powerful and actionable ideas on consumer confidence – and failing to take advantage of this technology puts your company at risk of losing market share to competitors that are leveraging these insights.
Below, you’ll find a number of applications of social data.
The conversations generated on social media occur incredibly quickly, meaning that they offer candid and spontaneous customer opinions. In contrast, many of the other commonly used data sources like as point of sale/transaction reports, or customer surveys, have significant lag time.
With an effective social listening tool, It is now far easier for brands to take advantage of the immediacy of social media comments in order to measure the success of products, services, and launches. In turn, This immediacy enables real-time feedback on existing campaigns, so marketing professionals can optimize and adjust current offers, or feed the planning process for future campaigns.
Customer Satisfaction: Responsiveness and Personalization
Access to accurate, real-time data allows for more agile decision making made with a greater degree of personalization, so that responding to the needs and concerns of customers is faster and more effective. This offers excellent opportunity to increase overall customer satisfaction and brand loyalty.
Highly Targeted Messaging and Data Accuracy
In addition to increased speed in terms of response time, the relevance and accuracy of social data is very high. On social media, consumers tend to talk more honestly about a brand or its products when they express their praise or dissatisfaction. These insights are not easily obtained through standard data collection methods, like a structured survey for example.
Monitor the Competition and Develop New Strategies
Taking advantage of social media analysis makes it far easier to monitor competition, opportunities, and threats within the market. Keeping track of consumer behaviors with social media analytics helps you monitor consumers in various online environments and effectively determine which platforms are the most profitable – guiding the development of more informed social media marketing strategy.
Not Every Social Media Metric Should Be Prioritized for Every Objective
There is a tendency to try to measure everything, however there is no need to obsess over every conceivable metric. Observe only the metrics which matter – admittedly, there always will be some need for vanity metrics: likes, shares, followers, retweets, views, or re-pins. However, there are advanced monitoring measurements offered by social listening tools, including volume of mentions, sentiment, main domains, TOP authors, top keywords, and influencer identification. The relevancy of data will depend on the primary objectives of your organization.
If the objective is generating brand awareness, metrics like share of voice are an indication of brand visibility with respect to your competitors, and can be accompanied with an analysis of owned media across various social channels.
If want to increase engagement from customers or prospects, you must to be sure to track the number comments, shares, and trackbacks divided by total views. This can effectively can demonstrate the effect of a campaign or crisis management strategy.
To improve customer service, you might monitor brand mentions with negative sentiment of to determine pain points and then cross-reference this data with indicators like resolution time and satisfaction scores.
One of the most compelling aspects about integrating your social data into your business intelligence strategy is that you may customize the data as necessary in order to ensure its relevance and efficiency.
Putting Everything Together: Views to Clicks to Sales
Social media data must be standardized so that it has a common structure. The terms and phrases should conform to a common glossary. Storing this information within a social listening platform over time allows for different types of analysis over time, either in real time or over certain periods.
As mentioned earlier, we choose KPIs aligned with current business objectives so that they can be analyzed with more traditional KPIs like ROI and profit to associate actions on social media with sales volume, revenue increases or decreases, and other relevant metrics.
It’s true that combining qualitative data from social media with classic quantitative data that is hosted in the BI systems may seem difficult. However, as social data becomes increasingly standard information leveraged by business, it becomes more and more feasible to unite them – specifically with BI systems that manage structured and unstructured data.