Data silos of social media data.
Businesses like Bonduelle are collecting and measuring a heap of structured data, every day. But, it only accounts for 20% of insights gathered from customer interactions. That’s 80% of unstructured data that’s lost or ignored. Text-based data such as email, social media conversations, surveys, call center transcripts. Vital information about consumers’ behavior and journey.
Albane's case study demonstrates how Bonduelle, using our social listening platform, tackled the challenge of optimizing its online brand strategy. How it implemented the use of social media data with different teams - risk, sales, marketing, product, HR, PR.
“In our bid for tenders for a monitoring tool, the number one criterion was the ability to build synthetic dashboards, in order to be able to share information with the different areas of the business. To generate added value, you need to be able to model and share information in a simple and targeted way.”
David Llanes - Head of Business Intelligence, Crisis Management and Communication, Bonduelle (@LlanesDavid_)
Social media data - what, why, how
Let’s start by discussing why social media data is too important to ignore. What it is, what it brings, and how it can be collected.
Social media data collection gives brands the opportunity to gain in-depth knowledge of their customers, their industry, their competitors. Data-driven marketing is built on insights pulled from deep analysis of brands’ marketing campaigns, content, social media performance.
The right data will be the foundation on which a brand can build.
- Personalization of customer experience
- Segmentation and targeting groups of consumers
- Winning new customers
- Lead generation
- Product development
- Improved customer service
What is social media data?
The raw insights collected from your brand’s social media activity - using a social listening tool - is super powerful. Why? Because it’s unsolicited, and it’s free!
Exploit data from online, social media, and traditional press.
Social media data mining reveals how users engage with your content on social networks such as LinkedIn, Facebook, and Twitter - percentages, numbers, stats. It includes:
- Shares
- Conversions
- Likes
- Comments
- Impressions
- Mentions
You’ll have the customer insights you need to drive strategy and make critical business decisions.
What is it, exactly?
Content…. from your audience, your consumers, your industry, your competitors. Positive tweet. Negative Facebook comment. Both contain insights that will help you make crucial decisions regarding business operations.
How can I use social media data?
A heap of data is… just a heap of data.
It's the insights you gather that are important. What do these numbers mean to your company? What actions could be taken to boost KPIs?
You need to turn this pile of data into actionable insights so you’re able to make informed business decisions and improve the processes in other teams throughout your company.
Our Bonduelle case study shows how a global FMCG tackled its heap of data. Dig in!
How can you use social media data analysis? Take a look...
Audience segmentation
As consumers living in the digital age, we expect our customer experience to be personalized. An email campaign will include different styles of email, depending on the recipient. Are you talking to C-level, or lower-level employees? US or Europe? If you’re posting on social, which channels are the most popular with your audience? What content, trends, languages are they using?
Lead nurturing, scoring, attribution
If you’re using a marketing automation platform to manage leads, you’re working with data about website visits, email click-through and open rate. Social media data should also be studied to understand consumer behavior insights.
- Score your leads - clicking on a social post, clicking an email
- Personalize your lead nurturing - if your leads are liking a certain topic you’re talking about, hit them with more of the same
- Fine-tune your lead attribution - email, webinar form, download page, social media post - where did the conversion originate?
Personalized sales outreach
Get your social media data out of the silo and let your sales team go crazy. Personalized conversations with prospects are always going to bring more success. Monitor the behavior of a prospect and reach out for a one-to-one chat.
Engaging content experience
Customize the content experience according to consumers and prospects. Insights about what topic consumers are engaging with, what trends prospects are talking about, mean you can post similar and encourage more engagement.
A social listening tool will pull out insights about media types, topics, brand image.
Social media data will answer questions about your social media performance:
- Which social channels are bringing the most lead generation?
- Why posts are converting best?
- What type of content is resonating with users - clicks, shares, mentions?
How do I collect social media data?
Whatever tool you choose to use to collect your social data - Twitter Analytics, Google Analytics, social listening platform - you must ensure the data is shared across your company - sales, marketing, customer support, product. If it lives in a silo, it brings nothing to the table.
Collecting social media data insights.
Our social listening platform will pull out raw data and statistical insights so you can analyze every content post, campaign, social network, ad. Way more than how many likes or shares, it will let you track clicks and leads, find which social channels are working for your brand, which messages are bringing revenue. Social media big data will bring a measurable and positive impact on outcomes and productivity - personality insights of consumers, audience segmentation for targeting your message, market research about your product, competitive intelligence, brand awareness.
Bonduelle case study
Read our case study with Bonduelle and learn how, by using our social media listening platform, the company gathered its social media data. Breaking down the data silos scattered throughout the company, combining the data, and pulling out strategic information beneficial to all the different departments.
