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3 Tips for Incorporating Social into Your Overall Marketing

by: Dave Walters (@_DaveWalters)
09 July 2015

Social MarketingThe role of social has been undergoing a subtle but serious shift in the last 12 to 18 months. The most progressive marketers remain laser-focused on their top three to four social networks and are much better at creating right-sized content for each network based on very real engagement-driven ROI metrics that have now been in place a measureable period of time.

While the bar will continue to rise for great content, engagement and the resulting ROI, the smartest marketers are now thinking about social way beyond fully optimized publishing. They’re now asking themselves how social engagement should impact their segmentation – how the behaviors and actions of their customers and prospects should affect their bigger marketing strategy. In essence, they’re turning to social as a listening platform to inform who, how and when they deliver their best messages and offers to their exact right customer.

So if social isn’t just about outbound content flinging, then we need to think about how to integrate this new social data at scale. And clearly, we need to tie specific behaviors to specific people to get our behavioral-driven events truly optimized. Fortunately, a marketing automation platform is an ideal place to aggregate this deep information and expose it to an automation engine designed to drive those perfect communications.

Let’s look at three ways you might incorporate social into your overall marketing efforts:

1) Capture social sentiment to trigger rewarding customer communications.

If social listening is in your field-of-vision, then two things need to happen at scale: a) combing a specific user’s timeline or feed in real time, and b) the tracking of any brand mentions by keyword or hashtag. Once that’s complete, then the chosen tool will likely use Natural Language Processing (NLP) tools to process the entire text and assign values like positive, neutral or negative at the macro level – and specifically for each subtopic it extracts from the content. For an excellent example of what this looks like in real life check out AlchemyAPI’s demo page, and use their default values – or plug in your own URL or block of content.

So if we know a specific user posts something positive about our brand on Twitter, how cool would it be to have an automated “Social Influencers” campaign pre-built and ready to go? The automation flags the positive comment, we scan our purchase data to confirm they’re a paying customer, and we also know they’ve visited our blog three times in the last 90 days. Clearly, they’re having a good experience with our brand and products. That’s an ideal moment to trigger a “thank you” email to that person with a great advocacy offer, or if you’re in more of a B2B setting, a message to their account rep with instructions on reaching out personally.

A similar program might have slightly tweaked rules but focus on dissatisfied customers. So you’d be listening for negative sentiment, scanning your marketing system for open support cases, and then triggering a proactive reach out from support. In fact, you’re likely to get even more end-user creditability if you’re proactively addressing concerns than rewarding positive behavior, so don’t get hung up on a single way of thinking.

2) Use affinity data to inform your marketing strategy.

If sentiment is a moment-in-time indicator of user satisfaction or distress, then understanding a user’s complete field of affinities can be a powerful element to collect at-scale.

I see many publishing companies who are good at this in a traditional database sense – aggregating interest and affinity data to understand how they could cross-sell advertising between multiple publications. Think about the hard costs associated with creating and delivering a printed magazine on the monthly basis – you certainly wouldn’t start a new one without knowing you could cross-sell existing advertisers and know they’d have a positive experience.

How you use affinity data in your own marketing will vary based on your business. Most simply, you might be marketing to insurance agents and use an interest topic like golf to drive the right contest prize or social-sharing incentive (think: “Enter to win an all-expenses-paid round for four at Torrey Pines Golf Course”). Using affinity data to inform both your incentive strategy and third-party partnerships is a great way to tie together specific audiences with triggers you think will drive desired behaviors.

In a more advanced setting, you might subtly incorporate affinity into the primary image within an email campaign based on the value in a field in the database. An easy example is serving beach offers and imagery to users you know have shown interest in St. Croix and are into diving. Sending that recipient a message featuring romantic Belgian getaways during prime diving season in the Caribbean is likely to fall on the deafest of ears. Maybe you build custom imagery and calls to action for your Top 5 affinities, and see what conversions look like when you up your dynamic marketing game that significantly.

3) Leverage social to help find ideal prospects and accelerate database growth.

Social acquisition might be the premier channel for both list growth and new user acquisition in the next two to three years – especially as the pressure to monetize increases on all social sites. Let me explain.

While most of us know what combination of elements make an ideal customer (think: location + gender + positive social activity + previous spend + industry segment, etc.), there are many sites that have an equal view of their user base – and likely at a much larger scale than you. Specifically, I’m thinking about Twitter’s 300 million active users, and Facebook’s billion-plus users who are insanely mobile and even more active. And I’m sure we’ll see Instagram follow in the next year or so.

Because they need to continually drive more monetization of their audience, both have turned to something called look-alike customer models. In short, marketers can upload a list of known users (with as much affinity and behavior data as possible), and the sites will run an analysis on their data and spit back a list of similar prospects – based on a proprietary mix of attributes. And yep, you pay to reach each new prospect directly, and in an ideal world you provide a value proposition so compelling they opt in to one of your nurture streams.

This matching of your known attributes with the hundreds of millions of social users can be gasoline on the fire of your acquisition strategy. It’s a great way to cast a wider net on affinities and only pay for as many prospects as you want to reach. Think retargeting-like precision, just on a social site where a user might be more willing to explore.

So now that we’re moving clearly into the “listening age” of social, the challenge becomes who can do this well – and at real-time, unlimited scale. A well-thought-out data structure that factors for key behaviors and sentiment – in combination with a sharpened view of paid media around look-alike models – is a solid beginning point for most marketers. Make sure you’re taking time to get off the hamster wheel of execution long enough to recognize and factor for these developing strategies.

Related Resources:

1) Webinar Recording: “5 Keys for Using Social to Drive Digital Marketing Success

2) Ebook: “Ultimate Guide to Assessing Your Digital Marketing Program

3) Blog: “How Marketing Can Help Provide the Social Support Your Customers Need to Buy Your Products


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