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Local Market Activation for Big Brands | SearchCon 2016
- 1. 1 May 12 & 13, 2016 | Breckenridge, Colorado
- 2. 2 Local Market Activation for Big Brands Nick Neels, Head of Local Search | @nickneels #SearchCon @NickNeels
- 3. 3 Local Market Activation for Big Brands #SearchCon @NickNeels
- 4. 4 Local Market Activation for Big Brands #SearchCon @NickNeels Each location has its own unique challenges regarding sales goals, campaign performance and competition. LMA is driving conversions at the local level.
- 5. 5 Local Market Activation for Big Brands #SearchCon @NickNeels 0 to 20,000+ brick & mortar locations “Locations” and “Markets” are interchangeable
- 6. 6 Local Market Activation for Big Brands #SearchCon @NickNeels Caring for all locations, but giving extra love to those in need.
- 7. 7 #SearchCon @NickNeels But does it exist? Can it exist?
- 8. 8 #SearchCon @NickNeels Yes, it can be a reality. You just need to know how to prioritize.
- 9. 9 #SearchCon @NickNeels It’s Christmas each year: You like everyone, but you spend more time with some than others.
- 10. 10 #SearchCon @NickNeels But I’m too busy, I don’t have time. There are just too many locations (target markets).
- 11. 11 #SearchCon @NickNeels Proactive planning can reduce reactive stress. You can do it with these 4 steps.
- 12. 12 #SearchCon @NickNeels #1 Stability Assessment #2 Performance Audit #3 Competitive Saturation Analysis #4 Priority Pitch
- 13. 13 #SearchCon @NickNeels Stability Assessment: Do the Research
- 14. 14 #SearchCon @NickNeels Stability Assessment: Make Friends, Gain Insight Store Number Stability Assessment 100 Open 101 Open 102 Open 103 Open 104 Open 105 Open 106 New Store (Nov 2016) 107 New Store (Dec 2016) 108 Future Closure (Oct 2016) 109 Future Closure (Dec 2016)
- 15. 15 #SearchCon @NickNeels Stability Assessment: Gain More Insight Store Number Sales 100 $ (5,000) 101 $ 12,000 102 $ (10,000) 103 $ 6,000 104 $ 6,000 105 $ 1,000
- 16. 16 #SearchCon @NickNeels Stability Assessment: Tier the Sales Data Store Number Sales Sales % 100 $ (5,000) 29% 101 $ 12,000 86% 102 $ (10,000) 14% 103 $ 6,000 57% 104 $ 6,000 57% 105 $ 1,000 43%
- 17. 17 #SearchCon @NickNeels Stability Assessment: Tier the Sales Data Store Number Sales Sales % Sales Tier 100 $ (5,000) 29% 1 101 $ 12,000 86% 3 102 $ (10,000) 14% 1 103 $ 6,000 57% 2 104 $ 6,000 57% 2 105 $ 1,000 43% 2
- 18. 18 #SearchCon @NickNeels Performance Audit: Campaign Health Check
- 19. 19 #SearchCon @NickNeels Performance Audit: Campaign Health Check Store Number LLM SEO PPC 100 3 2 2 101 2 2 3 102 2 2 1 103 2 3 2 104 3 3 2 105 1 1 2
- 20. 20 #SearchCon @NickNeels Competitive Saturation Analysis
- 21. 21 #SearchCon @NickNeels Competitive Saturation Analysis: Real Estate Team
- 22. 22 #SearchCon @NickNeels Competitive Saturation Analysis: Eyeball It
- 23. 23 #SearchCon @NickNeels Competitive Saturation Analysis: Scale It Location ID Group Lat Long High Competitor Count Group Lat Long Miles Apart 1 SlimGenics 39.815068 -105.081104 5 Jenny Craig 40.6667729 -73.475811 1658.9 2 SlimGenics 41.459875 -82.019666 4 Jenny Craig 41.861201 -87.975686 903.7 3 SlimGenics 41.681404 -81.296272 3 Jenny Craig 32.9411882 -97.1176371 648.9 4 SlimGenics 44.866012 -93.056131 5 Jenny Craig 34.074212 -118.37558 833.2 5 SlimGenics 44.8731253 -93.3254647 7 Jenny Craig 31.9941086 -81.1286575 1439.7 6 SlimGenics 39.749225 -105.000338 7 Jenny Craig 35.443561 -80.859494 1354.9 7 SlimGenics 41.119607 -81.47236 3 Jenny Craig 38.6702055 -121.1552884 862.6 8 SlimGenics 41.539973 -81.451364 5 Jenny Craig 42.2746069 -71.7501199 1734.0 9 SlimGenics 45.039171 -93.220902 4 Jenny Craig 39.8808624 -105.0942944 4.6 10 SlimGenics 44.9054244 -92.9240745 4 Jenny Craig 33.0154311 -96.7088565 660.8
- 24. 24 #SearchCon @NickNeels Competitive Saturation Analysis: Tier Competition Store Number Competition 100 2 101 3 102 2 103 2 104 2 105 1
- 25. 25 #SearchCon @NickNeels Priority Pitch: The Data Will Set You Free
- 26. 26 #SearchCon @NickNeels Priority Pitch: Multiply Across Store Number Sales Tier LLM SEO PPC Competition Priority Score 100 1 3 2 2 2 24 101 3 2 2 3 3 108 102 1 2 2 1 2 8 103 2 2 3 2 2 48 104 2 3 3 2 2 72 105 2 1 1 2 1 4
- 27. 27 #SearchCon @NickNeels Priority Pitch: Tier the Priority Score Store Number Priority Score Priority % Priority Tier 100 24 43% 2 101 108 86% 3 102 8 29% 1 103 48 57% 2 104 72 71% 3 105 4 14% 1
- 28. 28 #SearchCon @NickNeels Priority Pitch: The Trump Card
- 29. 29 #SearchCon @NickNeels Priority Pitch: The Trump Card Store Number Sales Tier Priority Tier The Trump Priority 100 1 2 2 101 3 3 3 102 1 1 3 103 2 2 2 104 2 3 1 105 2 1 1
- 30. 30 #SearchCon @NickNeels Priority Pitch: Pitch Priority
- 31. 31 #SearchCon @NickNeels Priority Pitch: Standing Ovation
- 32. 32 #SearchCon @NickNeels Execution: Less chaos, more control.
- 33. 33 #SearchCon @NickNeels By improving outliers, you create war stories. People remember stories more than stats.
- 34. 34 #SearchCon @NickNeels Better performance for local AND enterprise.
- 35. 35 Continue to work down the priority list. #SearchCon @NickNeels
- 36. 36 #SearchCon @NickNeels I’m not only talking about current clients, I’m talking about prospects too.
- 37. 37 #SearchCon @NickNeels Sales can leverage portions of this data to establish trust and credibility. Store Number Sales Sales % Sales Tier LLM SEO PPC Competition Priority Score Priority % Priority Tier The Trump Priority 100 $ (5,000) 29% 1 3 2 2 2 24 43% 2 2 101 $ 12,000 86% 3 2 2 3 3 108 86% 3 3 102 $ (10,000) 14% 1 2 2 1 2 8 29% 1 3 103 $ 6,000 57% 2 2 3 2 2 48 57% 2 2 104 $ 6,000 57% 2 3 3 2 2 72 71% 3 1 105 $ 1,000 43% 2 1 1 2 1 4 14% 1 1
- 38. 38 The Results: #1 Priority Plan Based on Data #2 Actionable List of Locations (Markets) #3 Outlier & Enterprise Improvement #4 War Stories that Spread #SearchCon @NickNeels
- 39. 39 Local Market Activation for Big Brands Nick Neels, Head of Local Search | @nickneels #SearchCon @NickNeels
Editor's Notes
- Compelling title, but what does it really mean?
- And at what scale?
- While not all brands have physical locations, the tactics I will discuss can also apply to target markets. Brands like American Express or Discover card do not have physical locations, yet they have target markets for their marketing efforts.
- But when you are talking about 20k locations, this seems somewhat impossible.
- Can this really be
- I’m just reacting to what my boss tells me to do, or to whichever franchisee is the loudest.
- Marketing doesn’t always interact with finance The number guys can be intimidating Put your fear aside, they are just people like you and me
- Work with the CFO, COO, or CEO to learn more about their expansion/contraction plans. I’ve seen some teams be so secretive of any closures that they don’t notify teams until one day before it closed, while other brands will be able to give you advance notice. We need to make sure we only focus on locations that will remain open, so we don’t waste our time. New store openings are good to keep on the radar for future marketing prioritization.
- Now that you are friends with the Bobs, you can also get store level sales data. Most brands have this data available up to the day or hour, but what you will want is to know how the locations are performing against their sales goals. This will allow you to get a sense of who the under and over performers are.
- This is the start of the priority model built in Excel. Any closures or new store openings have been omitted, and we will start to rank all the locations. First we will take the revenue figures, and rank them against their peers using the percent rank excel function.
- The easiest way I’ve found to prioritize hundreds or thousands of locations, is to boil all of the data down into a 3ish tier ranking system. So by creating a nested IF statement, we can assign a value from 1-3 depending on if the locations is a top performing (3), middle of the pack (2), or under performing (1). If you have 10 locations, this is easy to do manually, but if you have 5000, you will want to fully leverage a system like this.
- Now that we know how sales are for each location, we will prioritize locations based on performance.
- This is pretty straight forward. The concept is to tier performance dependent on which services you are currently running for the client.
- The third category we will add pertains to how much competition exists around each location. Often times, more brick & mortar competition in a market will result in greater digital marketing competition.
- Option 1, leverage the real estate team. They may have some usable data or models to help you rank the level of competition per location. If that doesn’t work…
- Eyeball it yourself. This may only work if you have a handful of locations or markets. Store locators will provide you the basic info you need. If you need to scale it…
- You can build it.
- Then you are done right? Wrong.
- Sales doesn’t always match performance or the handed down priorities.
- During the pitch you can actually point out the outliers that no one knew about and discuss the overall priority locations that may differ from other internal requests. That location you’ve been spending all of your time and money on may actually not be the one you should be focusing on.