{"id":961,"date":"2021-09-12T19:31:41","date_gmt":"2021-09-12T18:31:41","guid":{"rendered":"https:\/\/searchsolved.co.uk\/?p=961"},"modified":"2021-10-18T19:15:56","modified_gmt":"2021-10-18T18:15:56","slug":"how-to-automatically-map-your-internal-search-terms-report-directly-to-categories","status":"publish","type":"post","link":"https:\/\/searchsolved.co.uk\/how-to-automatically-map-your-internal-search-terms-report-directly-to-categories\/","title":{"rendered":"How To Automatically Map Your Site Search Report Keywords Directly to Category Pages"},"content":{"rendered":"\n<p>Today I&#8217;m going to show you how you leverage the internal <a href=\"https:\/\/support.google.com\/analytics\/answer\/1012264?hl=en#zippy=%2Cin-this-article\" data-type=\"URL\" data-id=\"https:\/\/support.google.com\/analytics\/answer\/1012264?hl=en#zippy=%2Cin-this-article\">site search report from Google Analytics<\/a> to automatically suggest mappings to category pages using Python and the popular <a href=\"https:\/\/maartengr.github.io\/PolyFuzz\/\" data-type=\"URL\" data-id=\"https:\/\/maartengr.github.io\/PolyFuzz\/\">Polyfuzz library<\/a>.<\/p>\n\n\n\n<p>Selectively mapping internal searches directly to category pages makes for a good user experience because it takes users directly to the page they were looking for.<\/p>\n\n\n\n<p>The script works by mapping keywords from the internal site search report to &#8216;H1s&#8217; from a crawl file. It uses the Polyfuzz library to fuzz match keywords to category &#8216;H1s&#8217;. Fuzzy matching allows matching to plurals, close matches and words found in a different order. <\/p>\n\n\n\n<p>This article will walk you through the code. It also includes a <a href=\"https:\/\/github.com\/searchsolved\/search-solved-public-seo\/tree\/main\/Internal%20Search%20Mapper\" data-type=\"URL\" data-id=\"https:\/\/github.com\/searchsolved\/search-solved-public-seo\/tree\/main\/Internal%20Search%20Mapper\">link to the source code on GitHub<\/a>, as well as a <a href=\"https:\/\/github.com\/searchsolved\/search-solved-public-seo\/blob\/main\/Internal%20Search%20Mapper\/Google%20Colab%20Notebook\/Map_Internal_Searches_to_Pages_v1_2.ipynb\" data-type=\"URL\" data-id=\"https:\/\/github.com\/searchsolved\/search-solved-public-seo\/blob\/main\/Internal%20Search%20Mapper\/Google%20Colab%20Notebook\/Map_Internal_Searches_to_Pages_v1_2.ipynb\">Google Colab Notebook<\/a> for ease of use.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The Problem We&#8217;re Trying to Solve<\/h2>\n\n\n\n<p>This eCommerce site returns a list of matching products when a user searches for &#8216;LED Lights&#8217;. <\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"862\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-25-1024x862.png\" alt=\"\" class=\"wp-image-964\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-25-1024x862.png 1024w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-25-300x253.png 300w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-25-768x647.png 768w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-25.png 1176w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption>List of products returned by the site search software matching the search term &#8216;LED lights&#8217;.<\/figcaption><\/figure>\n\n\n\n<p>This is not necessarily bad per say, but a <span style=\"text-decoration: underline;\">much better<\/span> solution would be to take the user directly to the Led Lighting category instead&#8230;<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"827\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-24-1024x827.png\" alt=\"\" class=\"wp-image-963\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-24-1024x827.png 1024w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-24-300x242.png 300w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-24-768x620.png 768w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-24.png 1172w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption>A much better result would be to take to user directly to the category is the search term matches unambiguously.<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Benefits of taking users directly to a matching category page:<\/h2>\n\n\n\n<ul><li>Additional subcategories for the user to drill down into<\/li><li>Focused category copy showcasing features, benefits and range highlights<\/li><li>Focused first page product selection<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Input Files Required<\/h2>\n\n\n\n<ul><li>Site search report from Google Analytics (Excel format only)<\/li><li>Internal_html report from Screaming Frog (CSV format only)<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Getting The Files: Site Search Report (Google Analytics)<\/h2>\n\n\n\n<p>The site search report is accessed via <em>Behaviour &gt; Site Search &gt; Search Terms<\/em><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"226\" height=\"296\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-26.png\" alt=\"\" class=\"wp-image-999\"\/><\/figure>\n\n\n\n<ol><li>Set a sensible date range to export (three months is usually ideal, setting it too far back runs the risk of stale data for dead stock etc).<\/li><li>Change the number of rows to the maximum available (or less if you prefer).<\/li><\/ol>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"331\" height=\"161\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-27.png\" alt=\"\" class=\"wp-image-1002\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-27.png 331w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-27-300x146.png 300w\" sizes=\"(max-width: 331px) 100vw, 331px\" \/><\/figure>\n\n\n\n<p>3. Finally, export the file in Excel format.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"488\" height=\"175\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-28.png\" alt=\"\" class=\"wp-image-1003\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-28.png 488w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-28-300x108.png 300w\" sizes=\"(max-width: 488px) 100vw, 488px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Getting The Files: Internal_html (Screaming Frog)<\/h2>\n\n\n\n<p>The Screaming Frog export is really straight forward. You just need to export the internal html as a .csv file as shown below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"491\" height=\"99\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-29.png\" alt=\"\" class=\"wp-image-1006\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-29.png 491w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-29-300x60.png 300w\" sizes=\"(max-width: 491px) 100vw, 491px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Script Output<\/h2>\n\n\n\n<p>The script outputs three different CSV files. All matches (contains partial and exact matches), all matches or partial matches. <\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"620\" height=\"71\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-30.png\" alt=\"\" class=\"wp-image-1008\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-30.png 620w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-30-300x34.png 300w\" sizes=\"(max-width: 620px) 100vw, 620px\" \/><\/figure>\n\n\n\n<p>The final output shows the search term from Google Analytics in column A, fuzzy matched to a category H1 from the crawl file. note some words are matched 100% even if they appear out of order. <\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"759\" height=\"605\" src=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-32.png\" alt=\"\" class=\"wp-image-1010\" srcset=\"https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-32.png 759w, https:\/\/searchsolved.co.uk\/wp-content\/uploads\/2021\/09\/image-32-300x239.png 300w\" sizes=\"(max-width: 759px) 100vw, 759px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Script Walkthrough<\/h2>\n\n\n\n<p>First we need to install pandas and the Polyfuzz library if not already installed.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pip install pandas<br>pip install polyfuzz<\/pre>\n\n\n\n<p>Do the imports.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">from polyfuzz import PolyFuzz<br>from glob import glob<br>import pandas as pd<\/pre>\n\n\n\n<p>Set the folder paths for the site search report and the crawl export.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># set the folder paths HERE for your input files!<br>ga_path = \"C:\\python_scripts\\Internal Search Mapper\"  # enter the path the the folder that contains your GA search terms export<br>sf_path = \"C:\\python_scripts\\Internal Search Mapper\"  # enter the path of the folder that contains internal_html.csv file<br>export_path = \"C:\\python_scripts\\Internal Search Mapper\"  # enter the path to export the output.csv file to<\/pre>\n\n\n\n<p>This code appends the file names to the paths set above.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># adds file names to the paths.<br>ga_path_file = ga_path + \"\/Analytics*.xlsx\"<br>sf_path_file = sf_path + \"\/internal_html.csv\"<br>export_exact = export_path + \"\/search-mapping-exact-matches.csv\"<br>export_partial = export_path + \"\/search-mapping-partial-matches.csv\"<br>export_all = export_path + \"\/search-mapping-all-matches.csv\"<\/pre>\n\n\n\n<p>Imports the internal site search report from Google Analytics. NB: File must be in Excel format.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># imports GA data using a wildcard match<br>for f in glob(ga_path_file):<br>    df_ga = pd.read_excel((f), sheet_name=\"Dataset1\")<\/pre>\n\n\n\n<p>Read in the Screaming Frog crawl. (I recommend removing any page you don&#8217;t want to map the internal site search report to. (e.g. remove product pages, if you dont&#8217; want to map searches there.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">df_sf = pd.read_csv(sf_path_file, encoding=\"utf8\")[[\"H1-1\", \"Address\", \"Indexability\"]]<\/pre>\n\n\n\n<p>Drop the H1 and internal site search report keywords to lower case for matching a deduping.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># convert to lower case for matching<br>df_sf[\"H1-1\"] = df_sf[\"H1-1\"].str.lower()<br>df_ga[\"Search Term\"] = df_ga[\"Search Term\"].str.lower()  # convert to lower case for matching<\/pre>\n\n\n\n<p>Try to drop non-indexable pages. (&#8216;Indexability&#8217; must be ticked in the &#8216;Extraction&#8217; heading of Screaming Frog settings.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># drop non-indexable pages<br>try:<br>    df_sf = df_sf[~df_sf[\"Indexability\"].isin([\"Non-Indexable\"])]<br>except Exception:<br>    pass<\/pre>\n\n\n\n<p>Clean up the dataframe by deleting the helper columns and remove any NaN values.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># delete the helper column<br>del df_sf[\"Indexability\"]<br><br># keep rows which are not NaN<br>df_ga = df_ga[df_ga[\"Search Term\"].notna()]<br>df_sf = df_sf[df_sf[\"H1-1\"].notna()]<\/pre>\n\n\n\n<p>Create two lists, one from the internal site search report, and another from the Screaming Frog crawl, ready to be fuzzy matches using Polyfuzz.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># create lists from dfs<br>ga_list = list(df_ga[\"Search Term\"])<br>sf_list = list(df_sf[\"H1-1\"])<\/pre>\n\n\n\n<p>It&#8217;s time to match the two lists using Polyfuzz!<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># instantiate PolyFuzz model, choose TF-IDF as the similarity measure and match the two lists.<br>model = PolyFuzz(\"TF-IDF\").match(ga_list, sf_list)<br><br># make the polyfuzz dataframe<br>df_pf_matches = model.get_matches()<br># keep only rows which are not NaN<br>df_pf_matches = df_pf_matches[df_pf_matches[\"To\"].notna()]<\/pre>\n\n\n\n<p>Let&#8217;s merge the GA data back into the dataframe Polyfuzz created.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># merge original ga search term data back into polyfuzz df<br>df_pf_matches_df_ga = pd.merge(df_pf_matches, df_ga, left_on=\"From\", right_on=\"Search Term\", how=\"inner\")<br><br># create final_df + merge original screaming frog data back in<br>final_df = pd.merge(df_pf_matches_df_ga, df_sf, left_on=\"To\", right_on=\"H1-1\")<\/pre>\n\n\n\n<p>Let&#8217;s clean and sort the dataframe some more.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># sort by opportunity<br>final_df = final_df.sort_values(by=\"Total Unique Searches\", ascending=False)<br><br># Round Float to two decimal places<br>final_df = final_df.round(decimals=2)<br><br># rename the cols<br>final_df.rename(columns={\"From\": \"Search Term\", \"To\": \"Matched H1\", \"Address\": \"Matched URL\"}, inplace=True)<br><br># set new column order for final df<br>cols = [<br>    \"Search Term\",<br>    \"Matched H1\",<br>    \"Similarity\",<br>    \"Matched URL\",<br>    \"Total Unique Searches\",<br>    \"Results Page Views\/Search\",<br>    \"% Search Exits\",<br>    \"% Search Refinements\",<br>    \"Time After Search\",<br>    \"Avg. Search Depth\",<br>]<br><br># re-index columns into a logical order<br>final_df = final_df.reindex(columns=cols)<br><br># drop duplicate keywords<br>final_df.drop_duplicates(subset=[\"Search Term\"], inplace=True)<\/pre>\n\n\n\n<p>Time to export the final CSV files.<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\"># export the final csv<br>final_df_exact = final_df.loc[final_df[\"Similarity\"] == 1]<br>final_df_partial = final_df.loc[final_df[\"Similarity\"] != 1].copy()<br><br>final_df_partial.sort_values([\"Similarity\", \"Total Unique Searches\"], ascending=[False, False], inplace=True)<br><br>final_df_exact.to_csv(export_exact, index=False)<br>final_df_partial.to_csv(export_partial, index=False)<br>final_df.to_csv(export_all, index=False)<\/pre>\n\n\n\n<p>Done! The script outputs three different files; Partial matches, exact matches and both match types combined.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Link to Github \/ Google Colab<\/h2>\n\n\n\n<p>Listed below are links to GitHub so you can play with the finished code. I&#8217;ve also included a Google Colaboratory Notebook which is even easier to use. (Just upload the crawl file and internal site search report from Google Analytics and the script will do it&#8217;s magic!)<\/p>\n\n\n\n<p><a href=\"https:\/\/github.com\/searchsolved\/search-solved-public-seo\/tree\/main\/Internal%20Search%20Mapper\" data-type=\"URL\" data-id=\"https:\/\/github.com\/searchsolved\/search-solved-public-seo\/tree\/main\/Internal%20Search%20Mapper\">Link to GitHub<br><\/a><a href=\"https:\/\/colab.research.google.com\/drive\/1Z2A0LJYABZ1kWjDiYRNdQG3-uLD7dUta\" data-type=\"URL\" data-id=\"https:\/\/colab.research.google.com\/drive\/1Z2A0LJYABZ1kWjDiYRNdQG3-uLD7dUta\">Link to the Google Colaboratory Notebook<\/a><br><br>Let me know how you get on by tweeting me&nbsp;<a href=\"https:\/\/twitter.com\/LeeFootSEO\">@LeeFootSEO<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Today I&#8217;m going to show you how you leverage the internal site search report from Google Analytics to automatically suggest mappings to category pages using Python and the popular Polyfuzz library. Selectively mapping internal searches directly to category pages makes for a good user experience because it takes users directly to the page they were [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":1430,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[12],"tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How To Automatically Map Your Site Search Report Keywords Directly to Category Pages - Professional SEO Consultants | Search Solved<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/searchsolved.co.uk\/how-to-automatically-map-your-internal-search-terms-report-directly-to-categories\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How To Automatically Map Your Site Search Report Keywords Directly to Category Pages - Professional SEO Consultants | Search Solved\" \/>\n<meta property=\"og:description\" content=\"Today I&#8217;m going to show you how you leverage the internal site search report from Google Analytics to automatically suggest mappings to category pages using Python and the popular Polyfuzz library. 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