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SEM Optimization + Growth Hacking - Small Changes = Big Results

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Casper Emil Sciuto Rouchmann

These slides cover a talk I gave at Conferize on the 4'th of September 2018. It covers: LinkedIn - Exclusions - Technology based targeting - Targeting your competitors customers & AdWords - Custom Intent Audiences - and how to use them - Pay pr. conversions (and how to trick the system...) If there's any questions or anything feel free to reach out to me. Casper Rouchmann Traffic Manager // Growth Hacker @ Templafy

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1 SEM Optimization + Growth Hacking Small Changes = Big Results
• 1) Practical • By the end of this session, my goal is to have taught you concrete tools that you can go home and apply to your business • 2) Mindset • These ‘tools’ / ‘hacks’ / ‘methods’ can be applied to multiple things, and my goal is to open your mind to do so… 05/09/20182 Why are we here?
• LinkedIn – a door to endless opportunities • Exclusions (Simple) • Technology based campaigns (Medium) • Targetting your competitors reviewers (customers) (Advanced) • AdWords • Custom Intent Audiences (Simple – yet very powerful) • Pay pr. Conversions Display advertising (Medium) 05/09/20183 Agenda
• Why are they important? • Stop wasting money on people we have already sold to • Stop wasting money on the wrong users (your own employees, competing product suppliers etc.) • You can exclude based on contacts (emails), or company names. Be creative. 05/09/20184 1) LinkedIn – Exclusions (Simple)
• Your list should look something like this: 05/09/20185 Example: Excluding your own customers
05/09/20186 Start excluding! #SavingMoney – Simple.
• Wouldn’t it be cool if we could target people who use a specific technology? • We can – and it’s surprisingly easy. • It doesn’t work in 100% of the cases, but it is extremely powerful • What do you need? A good B2B marketing/sales intelligence program. • I’ve been using Discover.org, but you can also use DataNyze or similar tools 05/09/20187 2) Technology based targeting (Simple)
05/09/20188 Do an advanced search based on technology being used by companies in the database (In this example, I am using Data Storage Systems + use Capterra/G2Crowd as a reference point)
05/09/20189 You get a list like the one below:
• I usually recommend an audience of around 100.000-150.000 people • And my favourite filters (for Templafy) are: • Job function • Seniority • Company size • Now you can make ads that specifically focus on the fact that they’re using a specific product. • (This campaign gave us one of our lowest cost pr. leads ever) 05/09/201810 Now use the natural power of LinkedIn + highly relevant content
• In SaaS (Software as a Service – duh) we’re often dependent on review sites, such as Capterra, GetApp, G2Crowd or one of their million friends… • That’s a lot of customer information just sitting there. • So the question was initially: How do we target these people at scale? • Full credit goes to Gilles De Clerk – I merely perfected his methods • The example I am about to show you is based on Capterra, but can be used with any website that provides you with: • First name • Last name • Company name 05/09/201811 3) Stealing Customers from Competitors (advanced)
• Example based on Zapier (#FavouriteTool) • With Capterra, we also get job title and industry 05/09/201812 What information do we have?
• Many tools out there (some more fancy than others) • DataMiner is a free Chrome Extension that does the job. • Create a new recipe, and let’s get started (you can watch this instruction video on how to: https://www.youtube.com/watch?v=DAMiHZauQDI) 05/09/201813 How do we do it? Step 1: Create a scraping recipe with Recipe Creator
• Open Dataminer, and select the recipe we’ve now created • If you do it correctly, you should get something like this 05/09/201814 Step 2: Scraping time
• The easiest way to get email addresses (which is our ultimate goal), is to collect names + domains. • We’ve got the names, now we need domains. • You can do this manually by running Company Names through Google, but we’re not into that non-automated life… 05/09/201815 Step 3: Match Company Names with Domains (using PhantomBuster)
• It used to be much more complex – but the nice guys @ Phantombuster have made a small guide for you to follow • You just need a Google Spreadsheet with company names in it (or a CSV file) – • Here we just take the data from our Dataminer sheet • We’re interested in the last part of our URL here (remember to enable sharing!) 05/09/201816 Step 3: Continued…
05/09/201817 Step 3: Script + Sheet matching
• Go to settings, and change it so that the number of retries is higher than 0 – I usually work with 10 • Why? Google blocks searches from IPs if they’re run in multiple succession – in this case the system uses another IP 05/09/201818
05/09/201819 Step 3: Laaaaunch • This process gives you an output.csv file • Which has all the company domains that we’ve been looking for
• The good thing about FindThatLead is that you can upload names+domains, and get emails in 80%+ of the cases • We can do two things with the data we’ve got: • ‘Domain Search’ to retrieve emails linked to a Domain • ‘Lead Search’ to find specific emails from First Name, Last Name and Domain 05/09/201820 Step 4: Use an email lookup system for cold-emailing (I’ve used FindThatLead)
• We need First Name, Last Name and Domain in separate columns • So we need to split the csv file. Go to Excel -> Data -> Text to columns, and use Space as the delimiter 05/09/201821 Step 4: Split the CSV file, so it can be read…
• We can get Phantombuster to help us here as well • Same approach, just a different script 05/09/201822 Step 5: Finding LinkedIn profiles
• Our sheet should look something like this when all is said and done 05/09/201823 Step 5: Final look at the sheet
• My favourite growth-hacking tool (I have quite a few…) is probably: Dux-Soup • It’s a little chrome-extension robot that helps us automate our actions on LinkedIn • It can do a lot of things, but we’re going to abuse it a little bit for what we need it to do now • We’re interested in the revisit function (It’s a pro-feature btw…) • You revisit profiles that you’ve auto-visited before – so we trick Dux-Soup into thinking it has already visited the profiles we’ve found for it. • All it takes is a CSV file with Dux-Soup export headers and first names/last names filled in 05/09/201824 Step 6: Unleash the Dux
• The template looks like the one below: 05/09/201825 Step 6: Unleash the Dux - continued Paste the Linked URLs in the ‘Profile’ column Dux-Soup will update the rest of the data once it revisited the LinkedIn Profile URLs in the ‘Profile column’.
• ‘Revisit’ Linkedin Profiles • How to: • 1) Upload the .CSV with the LinkedIn profiles • 2) Hit ‘Visit Profiles’ from the Dux-Soup Chrome extension UI • 3) After GDPR, LinkedIn changed a few things, so now we have to be connected to grab the PERSONAL emails of people – this requires you to connect, then re-apply the process • 4) Download results with ‘Download Data’ 05/09/201826 Step 6: Unleash the Dux - continued
• Why are we interested in personal email adresses? • Get this: a lot of the email addresses Dux-Soup will return are personal Gmail — addresses. • How so? • Simple: back when LinkedIn was taking its first steps, most people signed up with their personal email and never bothered to change their primary email addresses to their work email. 05/09/201827 Step 6: Unleash the Dux - continued
• From here on out, we can use the emails to create custom audiences on LinkedIn & Facebook • Utilize this to create Lookalike Audiences, and reap the benefits. 05/09/201828 Step 7: Create custom audiences – and profit
• Only works with Display Advertising • What can you do? • You can target specific URLs that people have visited. • Got it? • Target people who’ve looked at your competitors • Or people who’ve looked at specific events • Or what about people who’ve been reading about Digital Marketing? 05/09/201829 1) AdWords – Custom Intent & You
• Here’s an example of me targeting specific events that we’ll be participating in 05/09/201830 1) AdWords – Custom Intent & You
05/09/201831 2) AdWords – Pay pr. conversion • There’s 3 things that matter below: • Conversions • Clicks & Impressions • Cost • Hint: One of them is not correct.
05/09/201832 2) AdWords – Pay pr. conversion – continued… • Create a ‘normal’ display campaign • Pick a goal (you can also run it without) • Not all goals have access to this feature, and Google also requires a certain spend level • (probably won’t work on your 1-hour old account)
05/09/201833 2) AdWords – Pay pr. conversion – continued … • Under bidding, you can say ‘Pay for Conversions’
• Create a different landingpage, where you pick up the traffic and have very strict access demands • In our case, we had issues with HubSpot/Analytics tracking, so Google only saw 1 conversion, while we had approx. 55 conversions coming through • The goal: • Cheap traffic that we can re-target & segment on LinkedIn 05/09/201834 2) AdWords – Make the traffic hard to convert
Thank You 05/09/201835 Casper Rouchmann cer@templafy.com For guides, slides etc. Reach out to me on LinkedIn (You can use a bot, that’s cool)

More Related Content

SEM Optimization + Growth Hacking - Small Changes = Big Results

  • 1. 1 SEM Optimization + Growth Hacking Small Changes = Big Results
  • 2. • 1) Practical • By the end of this session, my goal is to have taught you concrete tools that you can go home and apply to your business • 2) Mindset • These ‘tools’ / ‘hacks’ / ‘methods’ can be applied to multiple things, and my goal is to open your mind to do so… 05/09/20182 Why are we here?
  • 3. • LinkedIn – a door to endless opportunities • Exclusions (Simple) • Technology based campaigns (Medium) • Targetting your competitors reviewers (customers) (Advanced) • AdWords • Custom Intent Audiences (Simple – yet very powerful) • Pay pr. Conversions Display advertising (Medium) 05/09/20183 Agenda
  • 4. • Why are they important? • Stop wasting money on people we have already sold to • Stop wasting money on the wrong users (your own employees, competing product suppliers etc.) • You can exclude based on contacts (emails), or company names. Be creative. 05/09/20184 1) LinkedIn – Exclusions (Simple)
  • 5. • Your list should look something like this: 05/09/20185 Example: Excluding your own customers
  • 7. • Wouldn’t it be cool if we could target people who use a specific technology? • We can – and it’s surprisingly easy. • It doesn’t work in 100% of the cases, but it is extremely powerful • What do you need? A good B2B marketing/sales intelligence program. • I’ve been using Discover.org, but you can also use DataNyze or similar tools 05/09/20187 2) Technology based targeting (Simple)
  • 8. 05/09/20188 Do an advanced search based on technology being used by companies in the database (In this example, I am using Data Storage Systems + use Capterra/G2Crowd as a reference point)
  • 9. 05/09/20189 You get a list like the one below:
  • 10. • I usually recommend an audience of around 100.000-150.000 people • And my favourite filters (for Templafy) are: • Job function • Seniority • Company size • Now you can make ads that specifically focus on the fact that they’re using a specific product. • (This campaign gave us one of our lowest cost pr. leads ever) 05/09/201810 Now use the natural power of LinkedIn + highly relevant content
  • 11. • In SaaS (Software as a Service – duh) we’re often dependent on review sites, such as Capterra, GetApp, G2Crowd or one of their million friends… • That’s a lot of customer information just sitting there. • So the question was initially: How do we target these people at scale? • Full credit goes to Gilles De Clerk – I merely perfected his methods • The example I am about to show you is based on Capterra, but can be used with any website that provides you with: • First name • Last name • Company name 05/09/201811 3) Stealing Customers from Competitors (advanced)
  • 12. • Example based on Zapier (#FavouriteTool) • With Capterra, we also get job title and industry 05/09/201812 What information do we have?
  • 13. • Many tools out there (some more fancy than others) • DataMiner is a free Chrome Extension that does the job. • Create a new recipe, and let’s get started (you can watch this instruction video on how to: https://www.youtube.com/watch?v=DAMiHZauQDI) 05/09/201813 How do we do it? Step 1: Create a scraping recipe with Recipe Creator
  • 14. • Open Dataminer, and select the recipe we’ve now created • If you do it correctly, you should get something like this 05/09/201814 Step 2: Scraping time
  • 15. • The easiest way to get email addresses (which is our ultimate goal), is to collect names + domains. • We’ve got the names, now we need domains. • You can do this manually by running Company Names through Google, but we’re not into that non-automated life… 05/09/201815 Step 3: Match Company Names with Domains (using PhantomBuster)
  • 16. • It used to be much more complex – but the nice guys @ Phantombuster have made a small guide for you to follow • You just need a Google Spreadsheet with company names in it (or a CSV file) – • Here we just take the data from our Dataminer sheet • We’re interested in the last part of our URL here (remember to enable sharing!) 05/09/201816 Step 3: Continued…
  • 17. 05/09/201817 Step 3: Script + Sheet matching
  • 18. • Go to settings, and change it so that the number of retries is higher than 0 – I usually work with 10 • Why? Google blocks searches from IPs if they’re run in multiple succession – in this case the system uses another IP 05/09/201818
  • 19. 05/09/201819 Step 3: Laaaaunch • This process gives you an output.csv file • Which has all the company domains that we’ve been looking for
  • 20. • The good thing about FindThatLead is that you can upload names+domains, and get emails in 80%+ of the cases • We can do two things with the data we’ve got: • ‘Domain Search’ to retrieve emails linked to a Domain • ‘Lead Search’ to find specific emails from First Name, Last Name and Domain 05/09/201820 Step 4: Use an email lookup system for cold-emailing (I’ve used FindThatLead)
  • 21. • We need First Name, Last Name and Domain in separate columns • So we need to split the csv file. Go to Excel -> Data -> Text to columns, and use Space as the delimiter 05/09/201821 Step 4: Split the CSV file, so it can be read…
  • 22. • We can get Phantombuster to help us here as well • Same approach, just a different script 05/09/201822 Step 5: Finding LinkedIn profiles
  • 23. • Our sheet should look something like this when all is said and done 05/09/201823 Step 5: Final look at the sheet
  • 24. • My favourite growth-hacking tool (I have quite a few…) is probably: Dux-Soup • It’s a little chrome-extension robot that helps us automate our actions on LinkedIn • It can do a lot of things, but we’re going to abuse it a little bit for what we need it to do now • We’re interested in the revisit function (It’s a pro-feature btw…) • You revisit profiles that you’ve auto-visited before – so we trick Dux-Soup into thinking it has already visited the profiles we’ve found for it. • All it takes is a CSV file with Dux-Soup export headers and first names/last names filled in 05/09/201824 Step 6: Unleash the Dux
  • 25. • The template looks like the one below: 05/09/201825 Step 6: Unleash the Dux - continued Paste the Linked URLs in the ‘Profile’ column Dux-Soup will update the rest of the data once it revisited the LinkedIn Profile URLs in the ‘Profile column’.
  • 26. • ‘Revisit’ Linkedin Profiles • How to: • 1) Upload the .CSV with the LinkedIn profiles • 2) Hit ‘Visit Profiles’ from the Dux-Soup Chrome extension UI • 3) After GDPR, LinkedIn changed a few things, so now we have to be connected to grab the PERSONAL emails of people – this requires you to connect, then re-apply the process • 4) Download results with ‘Download Data’ 05/09/201826 Step 6: Unleash the Dux - continued
  • 27. • Why are we interested in personal email adresses? • Get this: a lot of the email addresses Dux-Soup will return are personal Gmail — addresses. • How so? • Simple: back when LinkedIn was taking its first steps, most people signed up with their personal email and never bothered to change their primary email addresses to their work email. 05/09/201827 Step 6: Unleash the Dux - continued
  • 28. • From here on out, we can use the emails to create custom audiences on LinkedIn & Facebook • Utilize this to create Lookalike Audiences, and reap the benefits. 05/09/201828 Step 7: Create custom audiences – and profit
  • 29. • Only works with Display Advertising • What can you do? • You can target specific URLs that people have visited. • Got it? • Target people who’ve looked at your competitors • Or people who’ve looked at specific events • Or what about people who’ve been reading about Digital Marketing? 05/09/201829 1) AdWords – Custom Intent & You
  • 30. • Here’s an example of me targeting specific events that we’ll be participating in 05/09/201830 1) AdWords – Custom Intent & You
  • 31. 05/09/201831 2) AdWords – Pay pr. conversion • There’s 3 things that matter below: • Conversions • Clicks & Impressions • Cost • Hint: One of them is not correct.
  • 32. 05/09/201832 2) AdWords – Pay pr. conversion – continued… • Create a ‘normal’ display campaign • Pick a goal (you can also run it without) • Not all goals have access to this feature, and Google also requires a certain spend level • (probably won’t work on your 1-hour old account)
  • 33. 05/09/201833 2) AdWords – Pay pr. conversion – continued … • Under bidding, you can say ‘Pay for Conversions’
  • 34. • Create a different landingpage, where you pick up the traffic and have very strict access demands • In our case, we had issues with HubSpot/Analytics tracking, so Google only saw 1 conversion, while we had approx. 55 conversions coming through • The goal: • Cheap traffic that we can re-target & segment on LinkedIn 05/09/201834 2) AdWords – Make the traffic hard to convert
  • 35. Thank You 05/09/201835 Casper Rouchmann cer@templafy.com For guides, slides etc. Reach out to me on LinkedIn (You can use a bot, that’s cool)

Editor's Notes

  1. Why is this a step? A step towards what?
  2. Last sentence on this slide doesn’t make sense – should it be ‘to export heads’?
  3. Where have the numbers on this slide come from?