Measuring Your Personal Branding, Part 3- Data Assembly.png

Personal branding has been a hot topic since the dawn of the digital age. In the last 13 years, it’s become one of the most searched topics by people:

personal brand searches.png

However, one area of personal branding has remained elusive: measuring it effectively. Many personal branding guides, coaches, and textbooks advocate tracking little bits of data here and there, but we need a comprehensive, common-sense model for measuring our personal brand. In this series, we’ll build a model of measurement for a personal brand that anyone can use, constructed with free or very low-cost software.

Assembling Our Branding Data

In the last post, we set out this basic framework for measuring personal branding:

personal brand metrics journel.png

Let’s now begin to assemble the data in each of these categories. To do this, start with a spreadsheet. If at some point you’d like to visualize the data with Google Data Studio, I strongly recommend using Google Sheets.

Granularity

For companies and enterprises, we might need to extract and analyze data on a very frequent basis, perhaps as fast as daily or even twice daily. For our personal brands, that level of detail is probably unnecessary unless our business is also our personal brand. For most people, especially if you’re just getting started out, even monthly re-extraction of data is probably sufficient. If you’re a data junkie, do what makes you happy, but choose an interval that’s sustainable.

Sourcing The Data

I recommend putting together a spreadsheet workbook with separate tabs for each of the metrics we discussed in the previous post. Let’s look at where each of the data points come from.

Awareness Metrics

Branded organic search, such as people searching for “Chris Penn” comes from Google Analytics and/or Google Search Console:

search console.png

Mentions on social media come from our individual social media accounts; platforms like Twitter and Facebook have dedicated analytics pages:

twitter analytics.png

Mentions in press, blog posts, and other citations comes from Talkwalker Alerts and Google Alerts we set up to monitor our names:

talkwalker.png

Consideration Metrics

LinkedIn profile views come from our basic LinkedIn analytics; you’ll need to log in fairly frequently to keep a running tally:

linkedin.png

Website/blog visits (new visitors) comes from Google Analytics:

ga new users.png

Social media engagement, such as replies or comments come from our individual social profiles.

Evaluation Metrics

Key page visits on our website, such as our about page/bio comes from Google Analytics; we may want to set up a custom content grouping, but at the least, we can check page behaviors.

key pages.png

Asking others on social media about us comes from our social media monitoring efforts, be it the platforms themselves or separate tools.

Attending virtual events we’re part of also comes from social media monitoring.

Subscribing to our blog/newsletters comes from our email providers and/or blog RSS provider.

mautic.png

Commitment

Download a piece of content from us that requires registration comes from Google Analytics if we’ve set up downloads as a goal.

ga goal setup.png

Make a purchase from us comes from our eCommerce portals, service providers like Amazon, or other transaction monitoring, depending on where we sell our stuff.

gumroad.png

Directly message us and ask us for help comes from every messaging platform we’re on; we need to manually count this for now.

Hire us comes from… well, from whether or not you obtained a new job through your personal brand marketing efforts.

Loyalty

Returning visitors comes from our web analytics.

returning users.png

Active subscribers to our content comes from our email marketing system or our blog RSS provider.

mautic point scores.png

Ongoing conversations from identified customers comes from our personal CRM if we have one; otherwise, manually count conversations in your email.

Repeat purchases/downloads/commitments comes from our eCommerce/sales system.

Promotions/bonuses in an employment context comes from tracking your financial progress at your employer.

Evangelism

Continual increases in branded organic search comes from Search Console data.

Recommendations come from our LinkedIn profile data and other social networks where others recommend us. I suggest setting up curated collections of this data such as Twitter lists.

Referrals come from manual tracking in our email and messaging systems.

Endorsements come from LinkedIn and other social platforms where others can leave formal endorsements.

endorsements.png

Next: Building our Report

Once we’ve assembled all the data points above in a series of spreadsheets, we’ll be ready to assemble our report using Google Data Studio. Stay tuned!


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