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Marc Engelsman - Predictive Analytics: Making Your Data Work Harder for Your SEO and Other Content Marketing
- 1. Predictive Analytics: Making Your Data Work Harder for Your SEO and Other Content Marketing Marc Engelsman VP Strategy & Analytics @Marc_Engelsman
- 2. Or: Time To Put Down That Magic 8-Ball
- 3. @marc_engelsman3 Who Knew 13 Years Ago That Predictive Analytics Would Be a “Thing?”
- 4. @marc_engelsman4 Who Knew 13 Years Ago That Predictive Analytics Would Be a “Thing?” Source: Google Trends
- 5. @marc_engelsman5 Who Knew 13 Years Ago That Predictive Analytics Would Be a “Thing?” Source: Google Trends
- 6. @marc_engelsman6 “Predictive marketers are 2.9x more likely to report revenue growth at rates higher than the industry average” Source: Forrester Consulting
- 7. @marc_engelsman But Don’t I Need Big Data? 7
- 8. @marc_engelsman But Don’t I Need Big Data? 8 Source: Google Keyword Planner
- 9. @marc_engelsman 1:1 keyword : web page SEO: It’s All About the Keyword But… 9 Each page needs 60% unique content Limited # of webpages
- 11. @marc_engelsman Old Keyword Selection Process 11 Relevancy Frequency Competitioncy
- 12. @marc_engelsman New Keyword Taxonomy: Intent-Based 12 Source: Avinash Kaushik. Digital Marketing Evangelist, Google • “Close” users ready to act now DO Action • Broadcast to potential users Awareness SEE THINK • Engage users thinking about brand Evaluation
- 13. @marc_engelsman13 Do You Buy a Home or Buy a House? Source: Google Trends
- 14. 14 What Keywords Correlate With Buy a House? Source: Google Correlate
- 15. 1515
- 16. 1616 Source: Google Search Console
- 17. @marc_engelsman17 Source: Google Analytics Site Search
- 20. @marc_engelsman20 Source: KnowClick • Search is driving highest proportion of prospects who are coming specifically to apply. • The Top 3 topics of information sought by prospects are: 1) tuition & cost, 2) graduate program info, and 3) course information. • The “Tuitions & Cost” and “Financial Aid” pages both are very effective at helping visitors complete their tasks, but only a small portion of visitors find them. • Although tuition & costs and financial aid are among the most sought after information, less than 15% of prospects end up finding these pages. Predictive Insights:
- 22. @marc_engelsman What About Predicting Offline Conversion? 22
- 24. @marc_engelsman24 Source: Google Consumer Barometer
- 25. @marc_engelsman25 Source: Google Consumer Barometer
- 26. @marc_engelsman26 Source: Google Consumer Barometer
- 31. @marc_engelsman Summary 31 • You don’t need your own Big Data to do Predictive Analytics – use other peoples’ Big Data • For SEO, leverage predictive indicators to prioritize keywords based on search intent – not just search volume • For other forms of online/digital marketing and websites that don’t have hard online conversion capture, leverage data from other sources to predict behavior and success
- 32. @marc_engelsman Predictive Analytics Tools 32 • Google Trends www.trends.google.com • Google Correlate www.google.com/trends/correlate • Google Keyword Planner www.adwords.google.com/home/tools/keyword-planner/ • Google Search Console www.google.com/webmasters/tools/ • Google Analytics www.analytics.google.com Site Search Demographics • Think with Google www.thinkwithgoogle.com Consumer Barometer/Shopping Insights • Facebook Insights www.facebook.com/insights • Third-Party Research
- 33. @marc_engelsman And if all else fails, there’s always… 33 • Interactive Magic 8 Ball http://www.magicmgmt.com/gary/magic8ball/
Notes de l'éditeur
- See the predicted uptick here – I wonder if Google knew this was going to be a big topic here at Digital Summit
- Even though it’s the first recommended Ad Group in the keyword planner – and look at that $40.44 suggested bid. Good thing we’re talking about SEO primarily…
- Even though it’s the first recommended Ad Group in the keyword planner – and look at that $40.44 suggested bid. Good thing we’re talking about SEO primarily…
- …But buy a house is clearly gaining more ground in recent years and this information would lead you to predict better performance if you optimized for buy a house…
- What else should I optimize my real estate website for? Google Correlate can help predict what else someone searching for buy a house is also likely to be searching for – in this case CAN I buy a house correlates with buy a house searches which would lead you to consider optimizing for that phrase on a different page…
- Here’s another example of leveraging data to predict SEO value – USciences is a specialty university in Philadelphia focused on pharmacy and other medical professions including physical/occupational therapy – looking at Google Search Console data can tell us what unbranded keyword queries led visitors to the website – the list is what you would expect and alone might lead you to optimize for these terms
- Here’s another example of leveraging data to predict SEO value – USciences is a specialty university in Philadelphia focused on pharmacy and other medical professions including physical/occupational therapy – looking at Google Search Console data can tell us what unbranded keyword queries led visitors to the website – the list is what you would expect and alone might lead you to optimize for these terms
- However, looking at Google Analytics Site Search data reveals a deeper intent for some of the searchers including physician assistant and tuition/financial aid - but this only tells us what they did – not who they are or why they did it What was the intent of these visitors? What else were they looking for? But this data only tells what visitors did – not who or why
- To get to the who/why, we enlisted our partner KnowClick – their process is to align site intercept surveys with clickstream data to connect the dots between intent/expectation and website behavior
- So now we can differentiate who came to the website…
- …and some key intent and behavior data to predict what keywords would be good to optimize around… in this case prospects came to the website looking for three things with tuition/cost being one them. The good news here is those pages were very effective in helping visitors complete their tasks but only a small group of people were finding them – less than 15%...knowing that these pages were an important part of the prospects journey and were predictive of conversion led us to decide we should optimize for financial aid…
- And we did – as you can see here in this screen capture of USciences financial aid
- USciences good example where there is online conversion What if your conversion point is offline – what online behaviors predict offline success? Example: Website uses Store Locator as proxy for predictive intent but KnowClick research reveals that sometimes it’s actually predictive of “not” going further
- SCG Princeton website Website does not have reservation capability built in uses third-party system for online and call management Online-to-offline tracking not possible Where else can we go to get predictive insight?
- What sources do shoppers use when looking for local food information – search and social So I lied when I said you don’t need big data – should have said you don’t need your own big data because Google and Facebook and others have enough big data for you to use
- What do shoppers up to age 34 use – search-social
- What devices do these shoppers up to age 34 use for research?
- Compared with Google Analytics website visits shows the 25-34 age group tied for largest cohort
- Ages 25-34 were among the highest engaged people with the Facebook page -
- So we proposed testing using Facebook ads to target millennials specifically based on the predictive data captured before
- The click results from the ad show we are reaching our target audience and they are responding with the most engagement as we predicted – what we didn’t predict was that men would be 50% of the engaged clickers (the data from Google Analytics and Facebook Insights showed more of a 60% women/40% men split)