Offers, promotions, and product pricing are monitored in real-time as changes are made by advertisers, with hourly reports and alerts available.

Reports contain offers found in SEM ad copy text, on shopping engines, in PLA’s, and on landing pages.

The Search Monitor crawls online ads looking for the keywords you entered into the system. You have two ways to provide these:

1. Custom Keywords

Enter your own list of ad monitoring keywords into the platform, from 1 to a million. Include every variation you’d like monitored (see examples below). Change the list as often as you need. Don’t worry, these keywords stay within the walls of your account.

Importance of monitoring Twitter for affiliate activity

• Your affiliates will use any tool at their disposal to drive sales, and Twitter has become a favorite one
• Just like with a search engine ad, affiliates display an advertiser’s URL or brand name in their tweet but then send the clicker through their affiliate link (for the sale credit)
• All affiliate managers need a tool that monitors tweets every day of the year and allows the user to easily notify affiliates or vendors that a rule violation is occuring

What The Search Monitor captures for affiliate activity on Twitter

We have the data that demystifies the PLA!

PLAs are the talk of the town for retail search marketers and aren’t going away anytime soon. They are incredibly effective conversion tools but are often misunderstood. While marketers control the content of PLA ads through a data feed, the problem is a lack of visibility into which product is showing for a keyword query.

  gives you detailed click and spend data by vertical!

It provides historical paid search, organic search, and PLA statistics organized into vertical categories like Lodging, Apparel, Hobbies, Finance, etc.  Clients receive insight into unlimited competitors across 1,200+ verticals across millions of keywords for Google and Bing.

Here’s a list of the online advertising currently monitored by The Search Monitor. Contact us to learn more, as we are adding new ones each month.

• Search Engines:
  • Google (Google.com, Google Mobile, Google Search Network, Ask, AOL, & Google Contextual Network)
  • Yahoo (incl. Yahoo Mobile)
  • Bing
  • Baidu (China)
  • Yandex (Russia)
  • Naver (South Korea) Learn more
  • See one that is missing? Tell us!
• Shopping Engines:
  • Product Listing Ads on Google & Yahoo
  • Amazon
  • Shopzilla
  • Pricegrabber
  • Google Shopping
• Display Networks & In-App Mobile:
  • 60+ Display Networks, across 150,000+ publishers, & 50,000+ mobile apps
• Social Networks:
  • Twitter is monitored for affiliate links
• Affiliate/Partner Landing Pages:
  • Content monitoring of publisher landing pages for offer promotions like coupon codes, promo codes, credit card offers, or telecom offers

Global Footprint

Many other tools get their data from sources that are not focused on quality data. The stronger the data source, the more accurate the stats or trends will be, leading to better decisions and more predictable outcomes.

• Small Sample Sizes: Most data sources don’t use a large enough sample population
• Low Frequency: Most vendors do not sample keywords with enough frequency, and therefore, they don’t see all of the advertisers. Accuracy in advertiser identification requires intense daily keyword queries. Most vendors only query keywords once per month. Lighthouse queries keywords multiple times per day. Lastly, infrequent querying of keywords leads to inaccurate predictions of rank and ad copy variations. Without an accurate prediction of rank and ad copy variations, you cannot compute ad spend, which requires an adjustment to CPC as rank fluctuates and as ad copy relevance fluctuates.
• Inaccurate Click Data: Most vendors use a data source that cannot provide accurate click data. In order to compute essential metrics like budget, you have to capture clicks. Ad spend = clicks x cost per click.

Learn more about Our Precision Data and see the 13 reasons why our data is the absolute best in the business.

Precision starts with good data followed by time-tested algorithms pitted against real world experiences.

Good Data In