5 Tips for Scaling & Prioritizing SEO Data | BrightEdge Share14 (San Fran 08.22.14)
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Through working with an array of global enterprise-level clients, we understand the pain that SEOs encounter when understanding how to prioritize data properly and deciding where best to put their focus. A characteristic of large enterprise level sites is that they can have a large range of products and or services across a broad spectrum of niches. So with such a large amount of data, how do you then analyze it to see where the best opportunities lie? Even once you have made a decision on the best areas to prioritize, you still then need to question how you can do that whilst understanding seasonality and keeping on top of trends. The opportunity and forecasting tool in BrightEdge is a fantastic tool to assist with this however it is as only as good as the keywords and keyword groupings that you specify. This presentation, along with its accompanying blog post and FREE DOWNLOADABLE ANALYSIS TOOL explains some tips on how to ensure that you have a solid infrastructure in BrightEdge and how to prioritize your efforts when you cover a large number of areas in different regions. Well worth a read for any SEO Analysts out there responsible of setting the SEO strategies for large enterprises. Read more and download the tool for free at: http://us.searchlaboratory.com/blog/2014/08/brightedge-share-14/#sthash.wdKoIYZg.dpuf
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5 Tips for Scaling & Prioritizing SEO Data | BrightEdge Share14 (San Fran 08.22.14)
- 1. Company logo 5 Tips – Data, scale & prioritization for SEO - At the enterprise level
- 2. Chris Attewell SVP Americas
- 3. SEARCHLABORATORY 35 languages Global scale Organic SEO Content marketing CRO Online PR Paid SEM RTB Display
- 4. Enough about us… Company logo (white)
- 6. Where do we focus? ‘jackets’ Ave position 3 8,100 searches Ave order val - $80.00 ‘shorts’ Ave position 8 49,100 searches Ave order val - $40.00
- 8. KW focus is too vague KW Strategic
- 10. Data sources
- 13. TIP #1 - Spotting new KW groups maxi dresses Impr. Clicks Av Pos 18,123 1,800 3.5 Impr. Clicks Av Pos 420,123 61,800 5.5 Sum data separately *maxi* & *dresses* + maxi skirts + maxi dress + black maxi dresses + dresses + peplum dresses + red dresses 22,228 1,950 2.5
- 14. TIP #1 - Spotting new KW groups Titles ‘Category name | Brand.com’ ‘Category name | Brand Online’ womendsrsehsoses online sneaker store
- 15. TIP #2 - Spotting issues with ‘words’ ‘uk’ less than expected share of impressions lower ave pos … however, site ranks well for unmodified version search term
- 16. TIP #3 - Mining long tail De-dupe with current list of BrightEdge KW’s - & review
- 17. TIP #4 - Grouping for seasonality / trends
- 18. TIP #5 - Prioritizing international markets
- 19. Takeaways – Starter KW DB sheet
- 20. Thank you! http://bit.ly/searchlabs14 @searchlabs
Editor's Notes
- We are a global digital marketing agency specializing in organic and paid search. As part of this we also undertake: PPC SEO RTB Online PR SEM CRO Display And content marketing As I said before, we are global specialists – delivering campaigns in 36 countries and in 18 different languages
- Huge enterprise level sites: Lots of varied products and or services across a broad spectrum of niches Where is your time best served? How do you prioritize? How do you do that whilst understanding seasonality? How do you keep on top of upcoming trends across all these areas?
- Do we make some changes now in the hope we can improve position before the end of summer? Should I be even looking at these two areas? Which other areas should I be putting into this decision? Had to find that data individually from three different locations Still difficult because the season may be over before you know it
- What about all the other areas too???? Not enough information to make a sound judgment
- Looking at individual aren’t conducive to having a strategic overview
- NEED lots of data to make any sense of, and be able to prioritise for large sites
- I’ve got all this data in different places but how do I tie it all together easily????!!!
- Thankfully there’s a tool out there to help you make this prioritization, somewhat more manageable. **QUESTION to audience** Who uses the opportunity forecasting tool? If you don’t and you have a huge enter then do utilize it! However it’s only as good as the KW groupings you specify…. At the enterprise level there are often a huge number of ways to segment EG in fashion – is it garment / colour / material / size ???
- Subtle can often be accidental, leading to pages not ranking to their true potential Split terms into their constituent parts Understand new categories to segment (KW grouping)
- Modifier like online not normally a key focus area – volume is there are you making the most of those searches The modifier term ‘online’ signifies that the search user is more likely to convert online – ie not looking for a local store / walk in option Create the KW grouping, make the change…. and measure!
- **BACKGROUND** Because of penguin over-optimization is a much more sensitive issue than it used to be… By splitting out all the terms into individual components, understanding their performance and their overall average position can sometimes highlight things that you cannot see when analyzing conventional categorisations and individual KW’s **reveal** This example looks at the word UK… the site in question was actually a UK brand, however they were not registering as many impressions for ‘uk’ as you would expect and the ave position was relatively low After a bit of analysis it appears that Google is filtering them out because they are inadvertently spamming on the term UK **reveal reason** Via their size options!!! They put a prefix of UK on each size – however being on the UK site should prequalify the users expectation of UK sizes…. Again – create the KW grouping in BE, make the change and monitor the impact
- Long tail terms could unlock new trends and upcoming search terms in your niche WMT data - Sort on impression – take lowest 200 terms or so Paste up to top 200 into KW planner – get suggestions De-dupe with current list of BrightEdge KW’s Do periodically to: make sure tracking right terms in BrightEdge Keep on top Use peplum dresses as an example
- Paste WMT data into KW planner This part can be a bit labor intensive as KW planner is limited to 200 queries so perhaps get an interns help. Use excel ‘sparklines’ to give you a sense of seasonality / growth in certain search terms over the last twelve months Helps with planning content strategy ahead of spikes
- Export all KW data per market from BrightEdge Need to add a column or two and manipulate the data Turn into a table and PIVOT it!! Allows you to compare the markets at the top level and across similar KW categories For more drilled down it relies on your KW grouping names being the same across the different markets
- PICTURE SUBJECT TO CHANGE We’ve devised a little takeaway excel sheet for you to paste in your data, allowing you to analyse find new KW grouping