The Incremental Value of Paid Search
Posted by Administrator on Wednesday, June 28, 2006 · 1 Comment
The Incremental Value of Paid Search
What portion of sales driven by paid search advertising is incremental?
For catalogers, incremental PPC contributes 14% of total online sales, for retailers with bricks and mortar outlets 7%, for e-commerce pure plays 52%.
These are among the findings from the Rimm-Kaufman Group’s recently completed study on brand vs. non-brand search advertising.
Over 18 months, we studied a random sample of 50 marketers with significant search programs. We studied key performance indicators including closing ratio, order size, sales per click and paid search sales as a percentage of total site sales. For each of these dimensions, we sliced the data to divide the incremental and non-incremental effects of PPC advertising.
Defining “incremental”
Actually assessing incrementality for individual orders is nearly impossible. As a meaningful proxy, we divided each advertisers’ search ads into two buckets: those involving the advertiser’s brand and those that do not.
When a person starts their search with a brand name, they’ve already selected the retailer they wish to buy from. These searches largely reflect a retailers’ off-line marketing — catalog mailings, television, radio, print, word-of-mouth, and brand awareness. In most cases, brand searches are not incremental. (The situation differs for manufacturers who sell direct and compete with their distributors – for example, Lego Corporation advertising on “Lego”. We excluded such advertisers from our sample.)
Catalogers traditionally divide their orders into those from previous buyers and those from new buyers. But in the age of the web, the brand / non-brand categorization is equally important. A name’s presence on a catalog housefile is not an indicator of loyalty. When a prior buyer types in a non-brand search, she’s considering multiple merchants: that order is in play.
Study Results
Not surprisingly, the study reveals the strong influence of offline advertising. But while brand-driven search is a powerful lever for both catalogers and retailers, the opportunity for a growing a program on the more competitive terms is large. Non-brand search contributes 46% of all PPC sales for retailers, 62% for catalogers, and 97% for e-commerce pure plays.
The data also affirms that many catalog readers are “closed” in print before using search and the web as an order channel. Catalogers enjoy a 10.3% closing ratio on brand searches, but only a 1.2% closing ratio on non-brand searches. Catalogers should beware of paying commissions on brand searches. It’s the orders on competitive, non-brand searches that matter–and should command the bulk of expense and effort.
Marketers with a significant retail footprint should also expect channel spillover. For catalogers, sales $ per click is 7.5 times greater on brand($11.81) than searches than non-brand searches($1.58), for retailers the multiplier is only 2.3. For retailers, a large percentage of brand traffic is doing research online and then buying in their local retail store.
The study also provides findings on how competitive non-brand search contributes across 11 categories of goods sold, and assesses its value by business types and size. For a look at the study data and more key findings, see the Non-Brand Study Data Set.
Give Your Search Marketing Campaigns a Checkup
Posted by Administrator on Thursday, June 1, 2006 · 1 Comment
Introduction
For many catalogers, pay-per-click (PPC) search represents the largest line in their web marketing budget. Just as you should visit your dentist twice yearly for a checkup, so should you conduct a routine search marketing audit every six months or so. Regular checkups ensure your PPC campaigns stay healthy, whether managed by an agency or by an in-house team.
A PPC audit has three components: a sales data audit, a cost data audit, and an economic performance audit. The two data audits make sure you’re working with accurate numbers, and the performance audit makes sure your campaigns are running efficiently.
My firm manages paid search campaigns for catalogers. Conducting several of these audits for prospective clients each month, we’ve observed a wide menagerie of problems. Some of the checks suggested in this article seem basic. They are. However, all of the checks correspond to real problems we’ve observed in real campaigns, so we recommend following the full process.
PPC Sales Audit
First, audit your raw PPC sales data. Here’s how.
Pick a recent calendar month. From your search agency or in-house team, get the total sales attributed to PPC search over that month. Also get a detailed list of every order attributed to PPC search over that month, with order time and date stamp, order total, the search ad which drove the order, and the click time and date stamp.
Make sure reported total sales match the sum of the order totals.
Next, from your order management system, obtain a detailed list of every order taken through your website over the month. For each order, pull order time and date, order total, and the marketing channel credited with the sale (unknown, search, affiliate, email, etc.)
Compare the two order detail lists in Excel, matching orders by date, time, and amount.
You should be able to find every search-attributed order within the full list of web orders–and those orders should be credited to paid search.
If you find orders on the PPC list which are assigned to a non-PPC marketing channel on the all-web list, that’s a red flag.
This is “double counting,” where one order gets attributed to multiple programs. Dig into these cases, and see why the different systems disagree on what drove the order. Causes can range from the innocent (different tracking cookies, different order allocation windows, errors in tracking or allocation software) to the nefarious (malware, unethical agency tactics).
PPC Cost Audit
Next, audit your raw PPC advertising cost data.
Pick a recent calendar month. Ask your accounting department for actual advertising costs paid for that month to each major search engine (Google, Yahoo, MSN, Ask, etc). Your accounting folks should pull these costs from the actual advertising invoices received from the engines (if you pay by invoice) or from the actual credit card statements (if you pay by credit card).
Pull cost data for the same period for each engine by day from the engines themselves. Log in to the engine’s web management interfaces, or ask your agency to generate those reports.
Finally, gather cost data from your weekly search performance reports provided by your agency, your search management tool, or your in-house team.
For each engine, in aggregate and by day, compare these three sets of cost data — costs as invoiced by the engines, costs as reported by the engines, and costs as reported by your search performance reports. These should tie to within a few percent.
PPC Performance Audit
The sales and cost audits should give you confidence your search reports are based on reasonably accurate numbers. With that due diligence completed, next check that your search campaigns are running well.
The first check is to compare overall costs to overall sales. Compute this ratio. In aggregate, are your PPC campaigns producing sales efficiently? Is this ratio in line with your other online and offline advertising efforts?
Even if your search programs appear efficient in aggregate, this high level check can hide significant inefficiencies deeper down. Ask your agency or in-house team for phrase-level performance data. You want impressions, clicks, ad cost, average position, current max bid, sales, and orders rolled up by phrase over the last 60 days. Don’t settle for a report on just the top twenty terms–you need data on every phrase that had any cost or sales. If the team managing your search cannot (or will not) provide such data easily, that’s a big red flag.
Load the phrase-level data into Excel and compute three additional columns: A/S (ratio of advertising to sales), CPC (ratio of ad cost to clicks), and CTR (ratio of clicks to impressions). You can now perform several important checks quickly by sorting this Excel sheet different ways.
Brand vs. Non-brand
Sort the keyword-level cost and sales data alphabetically by keyword. Scan the list for your brand name (“Brand Name”, “BrandName”, “BrandName.com”) and its common misspellings, and pull those rows to the top. What fraction of your sales comes from your brand name? What fraction of your costs? Most retailers will find ads on their brand to be highly profitable. Great–but realize these sales come from customers already seeking you by name, and thus reflect prior advertising (catalog, radio, TV, web, word-of-mouth, etc.)
More importantly, consider the sales and costs from all the ads which don’t involve your brand name. Do the economics of this part of the portfolio also make sense? Make sure you are buying sales efficiently, with both brand and non-brand terms meeting your metrics.
In the catalog world, marketers carefully distinguish orders from new customers versus previous customers, and place more value on a new-to-file buyer.
In the search world, the analogous distinction is between orders following non-brand searches versus following brand searches. Even if a customer previously bought from you, the fact that she was doing general web searches in your product category just prior to her purchase suggests she was considering several merchants. Even if a customer is new to file, the fact that he reached your site and ordered following a search on your brand name suggests he was influenced by non-search advertising efforts. The first scenario is likely incremental business, the second scenario, not.
Most Expensive Terms
Sort the spreadsheet by descending total ad cost, bringing your most expensive search ads to the top. Are these crucial ads generating appropriate sales for their cost? Are the bids and average positions appropriate? Do you see low-performance phrases being overbid, or high-performance phrases being underbid?
Bidding correctly on low traffic phrases requires complex statistical algorithms. Bidding on the expensive high traffic terms doesn’t. Your in-house team or agency should be able to provide clear, jargon-free explanations of your bids on your top terms. If the bids don’t make sense on your most important terms, that’s a large red flag, and could reflect broader problems across the rest of the keyword portfolio.
Bid Logic
Remove the brand phrases from the spreadsheet, and sort the list by descending clicks. Group terms with more than 1000 clicks, aggregating their costs and sales. Group terms with between 900 and 1000 clicks, aggregating costs and sales. Repeat for each 100 click window, down to the last bin holding terms with under 100 clicks. Efficient bid management is always more challenging on low traffic terms, given the statistical variability around rare events. Regardless, you should expect each bin to have roughly similar efficiencies, as measured by their aggregate advertising to aggregate sales ratios.
Evaluating Your Phrase List
Look at your phrase lists, ensuring the words you are using to advertise your site covers the breadth of your products and services. A comprehensive phrase list will capture more traffic than a narrow list, and detailed specific terms often convert at a higher rate and enjoy lower CPC rates than more general terms.
Copy & Landing Pages
Check the ad copy and landing pages on your top 20 ads. Is the copy specific to the search phrase? Is the landing page appropriate? While it isn’t cost-effective to write custom ad copy for every search phrase in a large search portfolio, you should have specific focused copy on the top phrases.
Conclusion
Paid search is a highly complex marketing channel. Getting every detail perfect on a large campaign is impossible. However, you should expect the folks managing your search campaigns, be they in-house or at an agency, to keep your search campaigns in good overall health. Regular checkups, like periodic dental visits, take little time, allows early fixes to any discovered problems, and provide peace of mind when all is well.