Leveraging your first-party data for successful cross-channel marketing campaigns
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Here are the slides from our CTO, Angus Hamilton's talk at Search Leeds on how to use data for cross-channel marketing success.
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Leveraging your first-party data for successful cross-channel marketing campaigns
- 1. Angus Hamilton Leveraging your first-party data for successful cross-channel marketing campaigns
- 2. We are SEARCH LABORATORY SEO PPC International Analytics and Data Science Digital Strategy Social MediaProgrammatic Google Analytics 360
- 3. Agenda First vs. third-party data What is first-party data? How does it compare to third-party data? Using first-party data What are the benefits? How do you use it? Examples Next steps…
- 5. First and third-party data
- 6. First-party data Data you collect and own Reliable and relevant to your business Collected with the relevant permissions
- 7. Third-party data Data collected by ad tech/cookies Generic and less reliable/relevant Becoming harder to collect
- 8. Example – third-party data
- 9. Example – first-party data
- 11. Source: BCG, Digital Maturity Study, 2017 Advertisers who are successful at data-driven marketing are seeing revenue increases of as much as 20%, and cost savings of up to 30%
- 12. Using first-party data Create audiences to target your marketing effort Reduce spend on advertising to existing customers
- 13. What do you need? Skills Data Technology
- 15. What is an audience? Pool of users built from online and offline activity Used for targeting via online activity • Display • Search • Website personalisation
- 16. How do I create an audience?
- 18. Example case study 1 Fashion website Looking to maximise ROI from existing customers and generate new customers Offers free delivery and returns
- 19. User matrix Recent activity None Browsed Added to basket Bought Purchase habits Never bought Infrequent Frequent Lapsed frequent Average spend <£33 £33 - £99 £100 - 199 £200 + Buys items on sale? Unknown No Sometimes Always Returns % 0 – 25% 25 – 50% 50 – 75% 75 – 100% App usage Not installed Installed / doesn’t use Installed / browses Installed / purchases
- 20. Audience 1 – VIPs Recent activity None Browsed Added to basket Bought Purchase habits Never bought Infrequent Frequent Lapsed frequent Average spend <£33 £33 - £99 £100 - 199 £200 + Buys items on sale? Unknown No Sometimes Always Returns % 0 – 25% 25 – 50% 50 – 75% 75 – 100% App usage Not installed Installed / doesn’t use Installed / browses Installed / purchases
- 21. Loose frequency cap Audience 1 – VIPs New launches Refer-a- friend scheme Exclude from brand PPC Create similar audiences
- 22. Audience 2 – lapsed VIPs Recent activity None Browsed Added to basket Bought Purchase habits Never bought Infrequent Frequent Lapsed frequent Average spend <£33 £33 - £99 £100 - 199 £200 + Buys items on sale? Unknown No Sometimes Always Returns % 0 – 25% 25 – 50% 50 – 75% 75 – 100% App usage Not installed Installed / doesn’t use Installed / browses Installed / purchases
- 23. Audience 2 – lapsed VIPs Huge one-time discount Tight frequency cap Promote app install / usage
- 24. Audience 3 – regular returners Purchase habits Never bought Infrequent Frequent Lapsed frequent Average spend <£33 £33 - £99 £100 - 199 £200 + Buys items on sale? Unknown No Sometimes Always Returns % 0 – 25% 25 – 50% 50 – 75% 75 – 100%
- 25. Example case study 2 Lead gen site Looking to acquire new customers Typical sales cycle from 1 week to 3 months
- 26. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 27. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 28. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 29. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 30. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 31. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 32. Lead gen sales cycle Website visit Filled out form Real details Spoken to sales Qualified lead Proposal sent Closed won Closed lost Unqualified lead Fake details Phoned Left website
- 33. Advanced example
- 34. Life-time value prediction Event tracked Website Purchase
- 35. Gathering more first-party data Events Competitions Loyalty Schemes
- 36. Next steps Identify what first-party data you have Expand your data sources and refine your analysis Start using it – and innovate
- 37. Summary Gather data from both online and offline behaviour Use data analysis to segment your customers into audiences Use the tools available to bring that data together in one customer view Apply those audiences, test the results and repeat
- 38. Questions?
- 39. Contact us Leeds | London | New York +44 (0) 113 212 1211 info@searchlaboratory.com www.searchlaboratory.com/ Follow us on social media: facebook.com/searchlaboratory/ @searchlabs linkedin.com/company/search-laboratory/
Editor's Notes
- Live analysis of data being fed into GA Based on behaviour so far, use machine learning to predict what their likely future value will be Different audience buckets for the likelihood of conversion or the future expectation
- +similar audiences
- Action – restrict marketing budget
- Could be for legal, software, financial services etc. Mention salesforce integration.
- Basic remarketing Based on recency of visit
- Keep remarketing to them. They are likely in the market, just in the early stages
- Add to negative targeting for search and display. Don’t want to spend more money targeting someone unqualified.
- Keep targeting them to showcase credentials, award wins, latest case studies etc. Anything you can to push them over the line!
- Good work! Add to negative targeting for now. cross-sell products
- Unlucky. Depending on the industry, they might be valuable in future. If the service has a renewal date then you can market to them again before renewal. General advice: make sure people see different creative and have a variable experience throughout all of this. Don’t just tailor it to what you know about them but also tailor it to what they’ve already seen. Cross-platform remarketing: tag up based on where they came from previously
- Live analysis of data being fed into GA Based on behaviour so far, use machine learning to predict what their likely future value will be Different audience buckets for the likelihood of conversion or the future expectation