How to Create a Customer Persona Using Social Media Data?

90% of companies that exceed lead and revenue goals report using buyer personas to tailor services and products to their customers’ needs. How come only 15% of marketers who employ buyer personas find the concept “very effective?” There are several reasons why personas don’t work. Some brands create a single customer persona, thus ignoring the remainder of the market. Other companies build personas off their own biases or fail to keep them up-to-date. Today I’m going to tell you how to create a relevant buyer persona using Facebook, Twitter and LinkedIn insights.

Creating accurate customer personas with social media data

First and foremost, understand that there’s more to “social media” than Facebook, LinkedIn, Pinterest and Twitter. In fact, those are the top of the social media pyramid – and that’s where shallow conversations like, “I dropped my camera and now need a new one” are happening. Social networking websites are great for real-time B2C and B2B marketing; in case you pursue long-term goals, you should dive deeper into social data and join virtual communities to identify your customers’ pain points and make the necessary changes to your marketing strategy.

Twitter Analytics

With over 330 million active users, Twitter is the fourth most popular social media application – and a place where brands, influencers, and ordinary customers look for relevant content and engage in conversations.

Provided you have a business account on Twitter and share posts on a daily basis (according to CoSchedule, you should do it at least 15 times per day!), you have tons of user data right at your fingertips. How could you possibly use Twitter Analytics data to build a buyer persona?

If you click on the Audiences tab, you’ll gain insight into your followers’…

• Interests (technology, marketing, business, and finance, etc.);
• Demographics (gender, country, region, language, household income);
• Platform preferences (desktop vs. mobile, iOS vs. Android, wireless carrier).

This data can be used as a blueprint for your buyer persona.

The people who view my tweets, for instance, are mostly male, live in California, worship technology, prefer iOS over Android, watch sports channels and earn $75K to 99K or $150K to $200K annually. They are employed in a technical position, have a white collared job, or run their own business. Twitter says their homes are worth $100K to $200K; they bought a car less than two years ago and love premium brands.

In order to see if that’s true, I can check some of my followers’ profiles and see what content they share and retweet.

Facebook Analytics

With a Facebook business profile, you can monitor the number of people who viewed your page over a given period of time and learn their age, country, and language. By tracking your top-performing posts, you can identify your customers’ major topics of interest and figure out the best time to post content.

Now you can compare the data with your Twitter stats and add the missing info to your draft buyer persona.

Thus, a person who reads my Facebook posts is aged between 25 and 34 and is interested in digital transformation, IoT, and mobile app development.

LinkedIn Analytics

We’re going further – and here comes your LinkedIn company page. There you can view your visitors’ industries, company size, and job functions, as well as the region and country of residence.

If I ran an IT business, my ideal customer – let it be Dave – would be Senior Business Development Manager/Marketing Executive at a medium-sized company (51-200 employees) based in California. He’s 25-34 years old, makes around $100K per year and is interested in cutting-edge technology (the Internet of Things and Digital Transformation in particular). He has an iPhone, a relatively new car and a three-bedroom house.

The question remains, what problems does Dave face at work and how could my imaginary IT company help him take his business to the next level?

Here’s where virtual communities – i.e., LinkedIn groups and platforms like Business.com – come in handy.

You can join these communities to see which technology topics are trending there. On business.com, for instance, there’s the Expert Advice section to filter members’ technology questions by topic (mobile development, information technology, web). Same goes for LI groups, Reddit, Quora and other places where customers seek advice.

With the data, you can:

• Boost your content marketing efforts. High-quality content helps companies raise awareness among their target audience and convince potential customers their solution is the best. Yet, over 50% of all web content created by marketers goes unnoticed – simply because it doesn’t add value to consumers’ lives. Let’s get back to Dave, for example. He’s a non-tech person and wonders whether he should build a mobile app for his e-commerce business. What issues does he need to clarify? That’s right, the cost of developing a mobile application (and ways to reduce it). What else? Probably, the platform choice. Now it’s just iOS and Android – but he can’t really splurge on two native applications right away; is Xamarin any good? Finally, he wants to make sure mCommerce is not another gimmick. Once you know what troubles your audience, you can craft relevant content (blog posts, guest posts, infographics, SlideShare presentations, podcasts, and videos) and distribute it across multiple social media platforms including social networking sites, virtual communities, and news aggregators to expand your reach and educate potential customers;
• Become an influencer. Within a virtual community, an influencer is a link between experts and ordinary members who seek professional help. Thus, influencers filter out unimportant information and give their audience what really matters – and that’s where my IT company should be to influence Dave’s buying decisions directly;
• Create personalized marketing messages. 65% of consumers would think positively about a brand if it produced valuable, relevant and personalized content. 56% of customers expect companies to know their buying history. 75% of consumers are more likely to respond to an offer if it’s personalized. Modern customers are willing to share personal data with brands; the question is, are you ready to put this data to work?

82% of companies who take the time to design detailed buyer personas manage to create a better value proposition and convert more leads into customers. If you feel you can’t extract enough social data using the basic analytics tools, you can always turn to advanced solutions like Lexalytics or IBM Watson Analytics for social media. The latter, for instance, allows businesses to choose topics (building a mobile app) and themes (need professional help) they want to analyze, define relevant keywords and track customer sentiment – that is, how they’re feeling before making a purchase and what factors form their buying decisions. Perhaps it would make a great topic for my next article, right?