Data has become as ubiquitous as the air we breathe. Indeed, it often feels like companies are choking on it. IDC forecasts that the amount of data the world creates and copies in 2025 will reach 180 zettabytes. I’d never heard of a zettabyte before. It’s big. A trillion gigabytes big, if that helps you get your head around it. (Did it work?) With that much data, flowing into our software–and our social CRM database–every day, we have to find some way to control it.
The massive data collected by a social CRM can be used to personalize an individual’s experience, even as it reveals trends, influencers, moments of buying intent, and decision motivations that companies can use to market and sell more effectively on a large scale.
Lots of CRMs connect to social media and help you build your social database. You can find reviews and recommendations for the perfect Social CRM by using our Product Selection Tool or clicking the image below to get started.
1. Understand that social CRM data is as much about what you hear and as what you’re told.
Collecting the social data from prospects and customers who are in direct contact with your company via social media, email, or messaging is the easier part of social CRM data collection. Yet if you don’t actively listen and harvest relevant data from social media conversations that don’t directly tag your company or use your company name, you’re ignoring a huge chunk of valuable data.
Use social listening tools to hear what people have to say about your industry, and use those to help direct how you build, position and sell your own products or services. Your social CRM database is incomplete without collecting this sort of data that provides a greater context for your analysis.
2. Be selective about your data sources and your data.
Social media platforms and preferences constantly grow and evolve according to their users. You don’t need to climb every data mountain just because it’s there. That’s too much data, and it can quickly get out of your control. Be strategic about what data sources and data points have value for your business and focus on collecting those.
When you choose your data selectively, you no longer need to harvest data from every social media platform. Pay attention to those platforms that have a sufficient volume of statistically relevant data for your business. Take the same approach to filtering what data you collect: use filters to narrow the data pool by geographically or spending level criteria (for example).
3. Have a use plan for your data.
Specify what questions you want answered and what issues you want to learn about before you start collecting your data. Set use goals for what you want to get out of mining your social CRM data. Do you want to find influencers who will broaden your prospect pool? Do you want to identify more quickly and more accurately when prospects or current customers are ready to buy, and shorten your sales cycle? Increase the lifetime value of your customers?
Don’t collect the data that’s easiest to get just because you can get it. Clarify the business purpose first, which lets you specify the data that can help you achieve it.
4. Set standards for clean data and how quickly it can get processed.
Make your standards mutually agreeable: the business unit end-users of different types of data and IT teams responsible for collecting and cleaning it should set these standards together. You can take an service-level agreement (SLA) approach, which requires both sides to agree upon terms.
A collaborative approach to setting data use standards helps IT understand the sense of urgency on the business side, while helping the business side appreciate the time needed for implementation and the need for clean data. It won’t fully eliminate the tension of a big shared project and expect for the standards to shift as the business needs and technology to support them do. But having clear, accepted data cleaning and use procedures and standards will keep it to a manageable minimum.
5. Figure out how you’re going to capture and structure unstructured data.
Allowing unstructured data to slip through your hands isn’t even an option anymore. Social media conversations have always been unstructured compared to other digital text, and therefore difficult to parse. We’ve always been able to quantify social media actions like following, sharing, volume of comments, or how often a hashtag or keyword is used. However, these kinds of quantifiable actions don’t give a full picture of what’s happening on social media.
Traditional, quantifiable social metrics don’t offer insight into the attitude or sentiment of a social post or customer conversation with a chatbot. And these metrics completely overlook nontextual sharing on social media, like emojis, images, videos and audio clips. You need this unstructured data to get a more accurate picture of tribe motivations, opinions, and interests, which can then be used to more accurately identify the most valuable prospects, those who are ready to buy, and customers you may be close to losing.
6. Learn how to benefit from machine learning to glean insights.
Sometimes, we don’t even know what questions to ask. More social CRM and related tools are building artificial intelligence functions and services that analyze your terabytes of data to find the trends and insights that we poor humans simply don’t have the analytical capacity to process. AI tools can be used to analyze natural language (see point #5, above), identify conditions that are good predictors of a customer about to become very unhappy and very vocal, and uncover sales and prospecting opportunities.
The data itself doesn’t matter if companies can’t manage how it’s collected, validated and used. Without getting your social CRM database house in order, you’re both missing and misreading valuable insights. That’s frustrating and expensive, if not potentially deadly.
Elisa Silverman is a TechnologyAdvice contributor who follows these simple principles when writing: Never waste the reader’s time. Always be relevant — or at least be interesting. She’s been freelance writing for eight years, after spending years working in the technology and legal fields. You can connect with Elisa at www.elisasilverman.com.