6 Ways to Use Social Data for Targeted Marketing
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We live in a digitally connected world, and that means more people than ever are leaving digital signals for marketers to follow as they use mobile apps, social media, email in-boxes and so on. And here’s the good news. People actually want marketers to follow -- just not too closely. It’s all about being awesome with people, and that means being customer focused rather than obsessing over how personalized your marketing should be.
Social data offers marketers some of the best digital signals to follow for two reasons: 1) A lot of permission-based public data is made available to marketers through social platforms, and 2) Social data is full of simple and meaningful insights that can help you message to people at all stages of the customer lifecycle.
Here are five simple ways you can use social data for targeted marketing and turn some of those digital signals into customer-focused campaigns.
1. Targeting by events people follow
In July of 2015, Twitter announced the addition of Event Targeting for marketers. The built-in event calendar allows you to find trade shows, holidays, concerts and more, then gives you the ability to discover audience insights related to the followers of those events. For example, you can find total audience reach and even look at the tweets with the most engagement from the previous year. Once you’re done researching an event audience, you can launch a campaign that targets the event and combine your event targeting selections with other targets such as gender, language and device so you can reach different segments of the event audience.
2. Targeting your content marketing by interests and trends
If you want more of your content to be loved and shared, you can use social data to identify topics and trends that are highly likely to attract interest and virality. You can take a general approach by using Twitter Moments or Twitter Advanced Search to identify current topics and trends for rapid-response content. If you want to identify interests within smaller groups of specific customers, you can use Twitter’s Tailored Audiences analysis feature to identify interests based on an uploaded list. You can upload lists of email addresses, mobile phone numbers, Mobile Advertising IDs, Twitter usernames or Twitter user IDs, and Twitter will match them to users and show you a ranking of interests and basic demographics.
Use the top few interests to come up with your content topics for your specific audience.
3. Targeting by platform, then re-targeting based on audience attributes
The most straightforward way to target your marketing using social data is to choose a social platform and use the data provided by that platform to target their users with ads. For example, Twitter Ads and Facebook for Business provide advertisers with data to help get marketing messages in front of specific groups of users. When people on a specific platform click through to your website, you can use pixels to re-target them with ads on other websites based on the source of the click and the audience attributes you used to target the social platform ads.
4. Targeting by social influence
Spreading the word about your business is easier when you have fans and supporters who have a lot of their own fans and supporters. If you can find and build relationships with social influencers within categories or topics that point to your business, your marketing messages have a better chance of reaching extended audiences.
Use a service like Followerwonk by Moz or BuzzSumo to search for influencers within your existing follwer base or to find influencers who are external to your current connections. Then, tactfully include those influencers in your social-media marketing strategy.
5. Targeting emails with matched social data
Targeting and personalizing emails usually requires asking for information beyond an email address on a signup form or tracking email interactions over time to gather more information. Tracking activity takes time and asking for too much information on signup forms can negatively impact your signups. Matching emails to permission-based public social information allows you to segment your email lists sooner and send more relevant messages to groups with different characteristics.
Twitter’s Audience Manager can help you identify group segments within an email list, and even though you won’t identify personal data for each email address, you will be able to get a sense of topics and interests within specific email lists. For example, you could upload your @gmail emails and your @yahoo emails as separate audiences to see if you can identify differences in the mobile footprint within each group before sending a sweepstakes email offering a specific mobile device as a prize.
6. Targeted marketing across multiple social audiences
If you’re an advanced social data marketer, you’ve probably noticed that advertising through multiple social sites can really silo your marketing when you’re trying to reach people who use multiple social sites. That’s where social data application program interfaces (APIs) come in handy.
Many social sites offer data through an API, which allows you to pull in siloed data and combine it together with data in your data warehouse or marketing technology stack. If that’s too geeky a concept for your marketing brain, talk to your developers about using social data APIs for marketing or add a developer resource such as a growth engineer to your marketing team. That way, you can take advantage of this advanced form of data-driven marketing and even leverage API aggregators who can make easy work of combining different data sources together.
In summary, targeted marketing that leverages social data has big potential. Make sure you keep things simple, and don’t try to automate everything until you have identified the things that work with manual processes. It’s also important to make sure you’re thinking about what your customer wants instead of trying to change your customer to fit with what your company wants. Being customer focused is the key to success with all forms of data-driven marketing.