N-Gram Analysis in PPC: How to Uncover Profitable Keyword Patterns from Search Terms

N-Gram Analysis is a powerful technique for breaking down search queries into patterns of one or more words (n-grams) to analyze and reveal trends in user behavior. For PPC advertisers, n-gram analysis helps identify frequently occurring word combinations, offering insights into valuable keywords and phrases that drive conversions. By focusing on these patterns, marketers can refine their campaigns, identify negative keywords, and better understand the language their target audience uses.

In this guide, we’ll walk through the step-by-step process of conducting an n-gram analysis with practical examples.

Step 1: Gather and Export Search Term Data

Start by gathering search term data from your PPC platform, such as Google Ads. To do this:

- Navigate to Keywords > Search Terms in Google Ads.

- Set a date range that’s meaningful for your analysis (e.g., the past three months for recent trends).

- Export the data to a spreadsheet format, such as Excel or Google Sheets, so you can analyze and manipulate it easily.

Your data will include search terms, impressions, clicks, cost, conversions, and other metrics. These will provide the foundation for identifying profitable patterns.

Step 2: Preprocess the Data

Before breaking down the terms, clean up the data to ensure accurate analysis:

- Remove irrelevant columns: Keep columns such as Clicks, Impressions, Cost, and Conversions.

- Filter out irrelevant terms: Exclude branded keywords or keywords you know are irrelevant for your analysis, as they may skew your results.

- Format text: Convert all search terms to lowercase for consistency, since "Cloud Services" and "cloud services" should be counted as the same term.

Step 3: Break Down Search Terms into N-Grams

An n-gram is a sequence of “n” words from a given search term. For example:

- A 1-gram (unigram) of “cloud data storage solution” is [cloud, data, storage, solution].

- A 2-gram (bigram) is [cloud data, data storage, storage solution].

- A 3-gram (trigram) is [cloud data storage, data storage solution].

You can manually separate these or use a tool or script (e.g., in Python or R) to automate this process if you have many rows.

Example:

Search Term: "cloud data storage solution"

- 1-grams: "cloud", "data", "storage", "solution"

- 2-grams: "cloud data", "data storage", "storage solution"

- 3-gram: "cloud data storage"

Step 4: Count N-Gram Occurrences

Next, count the occurrences of each n-gram across all search terms. This will highlight commonly occurring word combinations and give insight into the language customers are using.

#### Example:

Suppose the following search terms appear in your data:

1. "cloud data storage solution"

2. "best data storage solution"

3. "affordable data storage"

Counting occurrences for 2-grams:

- "data storage" appears in all three search terms, so it has an occurrence count of 3.

- "cloud data" and "storage solution" each appear once.

These counts reveal which phrases are popular and may indicate a high level of user interest.

Step 5: Aggregate Performance Metrics by N-Gram

Now, aggregate performance metrics (like clicks, impressions, and conversions) for each n-gram to understand their value:

1. Sum up clicks, impressions, cost, and conversions for each n-gram. This helps you analyze which n-grams drive the most conversions, have high click-through rates (CTR), or are expensive but don’t convert well.

2. Calculate CTR and conversion rate for each n-gram. This will help prioritize the most profitable terms and identify patterns associated with valuable keywords.

#### Example:

If "data storage" has generated 100 clicks, 10 conversions, and a conversion rate of 10%, while "cloud data" has a lower conversion rate, this suggests "data storage" may be a more valuable n-gram to target.

Step 6: Identify Profitable Keywords and Patterns

Now that you have performance data, you can identify profitable keywords based on high-performing n-grams. Use these insights to refine your campaign:

1. Target profitable n-grams: Incorporate the high-converting n-grams into your keyword strategy by adding them as exact or phrase match keywords.

2. Add negative keywords: For n-grams with high impressions and low conversions, consider adding them as negative keywords to avoid wasting ad spend.

#### Example:

If “free data storage” has high impressions but low conversions, add “free” as a negative keyword to prevent ads from showing on queries that are unlikely to convert.

Step 7: Optimize Campaigns Based on Insights

With insights from your n-gram analysis, implement targeted adjustments to your PPC campaigns:

- Bid adjustments: Increase bids on keywords that contain profitable n-grams to maximize impressions and clicks.

- Ad copy optimization: Tailor ad copy to reflect the language from high-performing n-grams. For example, if “cloud storage solutions” performs well, consider using “solutions” rather than “services” in your ad copy.

- Landing page updates: Ensure the landing page reflects popular n-grams, which can help improve Quality Score and relevance.

Practical Example: E-commerce PPC Campaign

Let’s consider an e-commerce company selling tech products:

1. Their top-performing search terms include phrases like “buy affordable laptops,” “best laptops for students,” and “budget-friendly laptops.”

2. After conducting an n-gram analysis, they find “affordable laptops” and “budget-friendly laptops” are popular 2-grams with high conversion rates.

3. Based on these insights:

- They add “affordable laptops” as an exact match keyword.

- They adjust ad copy to emphasize affordability.

- They add “cheap laptops” as a negative keyword due to low conversions, reducing wasted ad spend.

Tools to Simplify N-Gram Analysis

There are several tools to help automate n-gram analysis:

- Excel or Google Sheets: Use functions like “Text to Columns” or “Split Text” to separate terms and pivot tables to count occurrences.

- Scripts: Write custom scripts in Python or R for large datasets, using packages like NLTK (Natural Language Toolkit) in Python.

- Third-Party Tools: Tools like Google Analytics, Keyword Hero, or Power My Analytics offer features to analyze n-grams for paid search data.

Conclusion

N-gram analysis is a powerful technique for understanding search term trends and uncovering profitable keywords. By analyzing patterns within search terms, marketers can identify valuable keywords and create more targeted, cost-effective PPC campaigns. It requires some data manipulation but can significantly enhance keyword strategy and ad performance, resulting in a higher ROI and more precise targeting. For any PPC manager looking to refine keyword strategies, n-gram analysis is a game-changing tool.