Benefits of Preferred Landing Page Management
Let us start by defining what a PLP is… PLP is an acronym for “Preferred Landing Page,” which is the URL that represents the page that you believe is the best page to be presented to a searcher based on the implied intent. Well, duh, isn’t that why we optimize specific pages? The reality is that while we do optimize particular pages to rank better, the reality is most ranking tools only tell you that you have “a” page ranking but not if it is the best page or the page you have been slaving over. In most cases the agency nor the client don’t care as long as they can show “a page” is ranking well.
I have been advocating using PLP Monitoring, or PLP Management, as some call it now since I started managing the SEO Program at IBM in 1998. I went into detail about the process at PubCon Vegas in 2004 and was greeted with skepticism. In the session, I have shown where we identified a huge problem at IBM where IBM Research pages often outrank our brand and product pages for a product or service. The research pages frequently beat us since their pages were keyword-rich, had links, and did not contain Flash or other creative elements that can negatively impact rankings.
At first, it did not really matter who ranked, just that “we ranked.” Once we broke out the reporting by Business Unit rather than a master IBM report, it started to matter which Business Unit and, more importantly, which page was ranking since we now held the BU Manager accountable for both rank and traffic increases.
The solution is simple: identifying the page with the best chance of converting the visitor to each keyword by Business Unit and mapping it to the keyword phrase. While it seemed simple on paper, it was painful to implement. This led to a robust Keyword Arbitration and Owner Management program around keywords across business units, which we can discuss in more detail later. We needed to understand the overlaps and the current state, so we developed a process where we would run simple rank reports and then pull them into a Microsoft Access Database to do a match to see if the “right page” was the page actually ranking. If it were, then it would pass and if not it would fail.
For those that failed, we would evaluate the higher ranking page and decide if it were the better page even if it was for a different business unit. We had a challenge when RFID technology became hot since we had 26 business areas in IBM that all wanted to rank for RFID, and of course, since it is a new technology, IBM Research often raked the best, which did not lead to leads or revenue. ? Our approach was to develop a cluster analysis of the phrase RFID and then parse out words to the appropriate business units. RFID hardware words went to hardware, RFID software went to software, and the generic category phrase RFID was assigned to a cross-BU content page where we could monitor the clicks to the different interest areas and update the message and banners on the pages based on what the searcher really wanted when searching on a generic category phrase.
What to Monitor?
So, how can you start reaping the benefits of managing PLPs at scale? Previously you could use DataPrizm which is the tool that we developed to manage this at scale. After fighting with agencies, brand-paid search teams, and Google threatening to take away our API, we decided to shut down DataPrizm a in 2022. The following analysis was shown on the dashboard in the solution but now you would need to work on it in another database setup.
Analysis 1:? No PLP in Top 10
This analysis shows us which of our most important keywords do not have their optimal page ranking. We focus on keywords that are in the Tier 1 classification and find all words were the PLP is not currently ranking in the top 10 positions.
Success Example:
A large travel company was ranking #1 for the keyword phrase ‘Easter Holiday Deals” and even had a 50% click through to the organic page. Unfortunately, there was a 98% bounce rate and no conversions. We detected this and found it was last years Easter holiday deals page and it contained no offers. After a quick 301 redirect the current page was ranking #1 and within 10 days they had received $60,000 in bookings that would have been lost had they not detected the less than optimal page ranking.
Analysis 2: PLP Ranking 11 – 15
This analysis focuses on keywords in the Tier 1 classification and finds all words where the PLP is currently ranking in the 11 to 15 potions of the search engine. This is the top of page 2. The idea is that these are low-hanging fruit that often need minor adjustments to get them to page 1. This is a great report to use to find quick opportunities for improvement.
Success Example:
A multinational software manufacture pulled this report and put their SEO team to work on a few of these pages and wer able to get 12 of them onto the first page just by adjusting title tags and getting some links from their partner blogs.? These pages generated over 35,000 in incremental traffic over the next quarter and and a significant increase in sales for these products.? These were words that were not on the “to do” list of the SEO team and by identifying them and quickly fixing them were able to show short term gains to their management team which bought them the trust to do this on a large scale.
Analysis 3: Non-PLP Ranking Top 10
This report focuses on identifying keywords where some pages other than the PLP rank in the Top 10 positions. This is a great report to use to find pages that are ranking that should not be ranking or often better PLPs.
Success Example:
A great example of this report happended in two parts. One thing I learned at IBM was that long after we stopped marketing and selling products our customers still use them. For a large computer manufacturer I went to Wikipedia and grabbed a list of about 50 products they had previously sold and added them to the tool. We used the Missed Opportunity Model to identify that there were over 1.2 million searches a month for these 50 product names. We identified there were 3 reasons for searching on the product name. The first, they needed support, second they wanted parts like power cords or docking stations and third, they wanted to upgrade to a new version of this model. Based on the opportunity analysis they created 50 pages (one for each product name) which offered the three options and loaded them. We added them as PLP’s in the tool and were able to monitor their performance. In about 2 weeks these pages replaced their Support PDF’s and the page ranking and traffic started to increase as well as revenue. At the end of 6 months they had generated about $400k in incremental revenue from parts, accessories and upgrades due to these pages. These words were added to paid seaerch as well as a team set up to develop pages for every product that was retired in the past 5 years.
Analysis 4:? PLP in Top 10
The analysis is the opposite of Analysis 1, where this time, we should determine which of the keywords are in the top 10. This analysis shows us which of our most important keywords which do their have their optimal page ranking but can also see if there is another page ranking higher.
No success examples for this report. This is just the “warm fuzzy” report that show what is working and included just because users wanted to be able to show what was working.
Opportunity Modeling and Business Case Development
It is wise to show the “Optimization Impact Value,” if we can get into the first page of, more importantly, the top 5 positions. What is the expected lift in traffic and conversions when that happens? We monitor the traffic and conversions from top-ranked pages with and without PLPs being the ranking pages. We are finding that there is often a 30% increase in clicks and a 50+% increase in conversions when the PLP is the page ranking the highest and ultimately on the first page. Since we have data for all words and pages, we are able to extrapolate the success of single pages.