Methodology for Qualifying Prospective Partner Brands Online

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Find Your Partner

Co-marketing with complementary brands is an age-old tactic and can produce a sizable return – particularly for brands that are interested in lead generation. Partnering on promotional offers brings a new customer base to the table for little (or no) additional cost while both brands can share all new leads resulting from co-marketing efforts. Finding the right brand to engage –with a desirable customer/fan-base– can be tricky. I’ve worked on campaigns where my client was super excited to have another brand ready and willing to activate their millions of  social media followers in a joint campaign. Then as the planning progressed, they looked closer at the prospective brand’s Facebook metrics and learned that the actual fan base was primarily made up of 14 year olds – half the age of their target demographic and with much less spending power.

Identifying and qualifying potential partner brands can be approached with a bit more rigor. I’ve put together a loose methodology that can help vet and quantify the best fit for partner brands based upon audience demographics and potential social reach.

Fit and Figures

The brand I was working with for this particular sweepstakes campaign had identified their target customer as being female, over 35 years old with $100k or more in household income. Pinterest stood out to me to be a great potential network for targeting women that matched the profile. Unfortunately, my client had no existing presence or credibility within the network. This provided a opportune time to align with another key brand that had an existing community presence. I started by pulling the top 50 Pinterest brand accounts by follower count and then quickly vetted them for compatibility with my client’s brand and alignment with the mix of activities/themes we were exploring for their various social campaign efforts.

Next, I  tallied the aggregate fan totals across Pinterest, Facebook, Twitter, and YouTube for each brand and added the numbers to the average daily unique visitors that visited their primary website. I equated this sum total as the brand’s ‘Reach’ of known public impressions (naturally I didn’t/couldn’t account for private lists, broadcast impressions or media distribution).

I then leveraged Quantcast‘s handy service to extract demographic data regarding the make-up of the site’s users for each brand. Quantcast measures visitor data against the internet average and then assigns a percentage value of whether the audience is above or below the index for a variety of criteria including income, age, ethnicity, even if the user is likely to have kids. I kept my focus on counting ‘females’, ‘over 35’, ‘earning over $100k’ and then added up all of the percentage points that exceeded the internet average (per brand). The resulting number was reflected as the ‘Match’ metric and provided a quick way to quantify, and prioritize, the fit of prospective partners.

Each potential brand partner was run through this analysis and the results were eye opening in some occasions and solidified earlier assumptions in others. All in all, we had a short-list of prospective partners to begin early partner discussions and deeper due diligence.

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About Author

My name is Daniel T. Wood. I am an experience strategist working in Portland, Oregon. I primarily write about digital trends including user experience, technology, culture and marketing. I can be reached at daniel@MIRA.agency

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