She let me know that “No, Kiko, this hasn’t always been a thing”. Without even meaning to, I had stumbled into something new.

I’ll take you through the process I went through to set up Google Shopping campaigns in multiple languages and give you some pointers based on what I learned along the way. Once you know it’s there, It’s actually really easy to do.

Create and Upload Your Feed

What led me to my discovery in the first place is the fact that I have an e-commerce client with a strong presence in Canada. They serve versions of their site in both French and English. One of our jobs this year has been to expand our Canadian search campaigns to include both campaigns in both languages.

While I was updating their older PLA campaign setup to the new Google Shopping campaigns I had the thought, “I should duplicate this feed and upload it in French.” The information was all there, so I replaced titles, descriptions and URLs to reflect the French version of the site.

With my French spreadsheet ready to go, I created a new test feed, selected Canada as my country and French as my language.  This option wasn’t always there, but fortunately for me, it is now.

After Elizabeth and I took a closer look, we realized that depending on what country we chose, we would essentially get their national languages. Here’s a quick rundown of the countries we found that allow for multiple languages.

• Belgium – French & Dutch
• Canada – English & French
• Switzerland – German, English, French & Italian

The basic rule you need to follow is that is that, for each country or language you want to target, you need to have unique pages listed in that language & using the correct currency for the country.

It doesn’t seem to matter whether it’s on a separate domain or a subdomain as long as it’s a unique URL and the data is correct. If you want more info, Google has a full rundown of the requirements for targeting each country here.

I uploaded my test feed, grabbed a cup of coffee, and checked the results when I got back (our feed is fairly small, you may have to go to lunch). After I had everything uploaded the way I wanted, I created a real feed and uploaded my products to it.

AdWords Implementation

I had everything set on the Merchant Center side so, obviously, the next goal was to set up my new French language Google Shopping campaign. At this point, I ended up taking one step forward, and two steps back, but I learned a lot.

It turns out that Google Shopping campaigns don’t actually have an option to target languages. For reasons I can only guess Google will give you the option of targeting a completely different country than your country of sale, but you can’t pick what language to target.

Because that makes sense.

What that gave us was one Google Shopping campaign, targeting Canada, that included both French and English products lumped together. That’s not really ideal when it comes to writing promotional text or having to bid for both languages at once.

Thankfully, when AdWords introduced Google Shopping campaigns, they gave us the tools to work around this issue in Custom Labels. We did have to use one of our custom label spots, but we used that custom label to tag each item with the language it was written in. After we tagged them all, we re-uploaded both the French & English Feeds in Merchant Center.

Once the changes were live in our AdWords account, we got busy creating two separate campaigns. We used an inventory filter in the campaign settings so that each campaign only received products in the language we selected, one for English, one for French.

With only a little bit of extra work we ended up with two campaigns targeting separate languages just like we originally intended. Until AdWords introduces language settings as an actual feature for Google Shopping campaigns, this work around will get you going.

So far, we have only tried this for Canada, but I’d love to hear from anyone else doing global e-commerce. Do you promote products in one of the countries that qualify? Have you tried promoting PLAs in multiple languages? How was your experience? Le me know!

Merci beaucoup!

**Photo By: Markus Spiske

The post Make Your Google Shopping Campaigns Multilingual appeared first on Portent.

Still, despite her best attempts at teaching me the value of plus signs, quotes and brackets, some habits die hard.

The wide net of broad match, though often shunned in favor of more stringent match types, still has its place in the world of paid search. However, as Google and Bing-Hoo race to loosen the elasticity of these matches, wrestling your matched queries into submission becomes a river of tears labor of love. Fortunately, there are ways to process low-relevance queries in bulk without need for any scripting chops or a surplus of free time.

Enter Fuzzy Lookup.

Fuzzy Lookup is an add-in for Microsoft Excel that simplifies comparative text analysis and allows for variable thresholds of output similarities. Such a tool has countless potential applications for anyone working with large sets of data. For our purposes, Fuzzy Lookup will enable us to prune our search queries using our bidded keywords as matching criteria. The output can then be used to build large sets of negative keywords and, ultimately, maximize the quality of traffic being driven by non-exact keywords.

Before we get to work, you’ll need to download and install the Fuzzy Lookup add-in from Microsoft. Once finished, open a blank Excel workbook and look for the Fuzzy Lookup icon in the ribbon of your Excel window. Salvation lies within.

To populate your workbook, grab a list of your bidded keywords and the corresponding search queries. It doesn’t matter if you pull these from reports or just download them directly from the AdWords UI, but keep your initial selection to one Ad Group. This method is capable of processing much larger lists of keywords, but a smaller selection will serve you well when setting up for the first time.

Paste each list in a separate worksheet, using descriptive headers like “Bidded Keywords” and “SearchQueries”. Once both are in place, highlight either list and click the “Format as Table” button in the Excel ribbon. Which style of table you choose is entirely up to you, but do remember to indicate that your table has headers. Do this for both lists, and then click back to your Bidded Keywords worksheet.

You should now have two worksheets, once with a table of raw search queries, and the other with a table of bidded terms. I know how exhausted you must be, but mop that e-sweat from your iBrow and let’s see this one through. “TEAM” on three!

There’s a tab in the Excel menu titled “Fuzzy Lookup”, and a button by the same name behind it. When you click the “Fuzzy Lookup” button, it searches out all tables within the workbook, regard less of how many worksheets are present. A sidebar control panel will appear, and you should see the Fuzzy Lookup has already Identified your tables.

I generally keep the Bidded Keywords table as my Left Column, and my Search Queries table as my right.

Now, because I have 23 queries that I’m looking to match, I’ve set the Number of Matches to exactly 23. Experiment with lowering this number as you explore the tool and see the difference in the results that Fuzzy Lookup returns. I also keep my “Similarity Threshold” just West of center at around 0.33. Again, the specific results you’re after may be hiding behind a different set of conditions, so give yourself some time to try out alternative settings.

Finally, if my Bidded Keywords table is on Sheet 1 A:A, then I’ll highlight Sheet 1 B1 and click “Go”.

Note: Make sure the “FuzzyLookup.Similarity” option is checked.

Above is a picture of the output I receive using my lists of Bidded Keywords and Search Queries. For a little extra flair, I’ve added color scales as conditional formatting.

With this information, I can use the similarity score both to identify similar terms I may consider actively bidding on, and to identify low-relevance queries that could find a home in a negative keyword list somewhere. No pulling and comparing reports, no manual examination of hundreds of queries, just a free plugin, some swift fingers, and a lot of leftover time.

So what do to with that time? Here’s a thought: VLookups. Try adding in engine-side performance data (CTR, CPA, Impressions, etc) and see what correlations you find. What is the similarity threshold beyond which your CTR takes a dive? What are the low-similarity but high-impression terms that are artificially deflating your overall CTR?

Go forth, geek out, and keep it fuzzy!

The post Harvesting Bulk Negative Keywords with Excel appeared first on Portent.

Now, I love my coworkers but they also set pretty high bar. When I inherited a major cosmetics account from my colleague Michael Weigand, I knew I had my work cut out for me, specifically in the holiday season.

Throughout the year I kept track on my progress versus Michael’s results. Call it friendly competition (I must crush him). In September I started doing Holiday season preparations. I found that while we were still producing similar levels of revenue, over time our ROI had started to dip.

I’m the dark blue line

When I started examining individual campaigns, I discovered that the most dramatic ROI changes were happening in our branded campaign.

The gap widens

When I looked inside the branded campaign, I found that the major workhorse of the campaign was the exact match version of their brand name. That’s not especially surprising to anyone, I’m sure. What was a little more surprising to me was that the impression share on this keyword was only at around 80%.

My campaign regularly spent under the budget I’d set for it and I’d never received a “limited due to budget” notice from AdWords. So I was a bit puzzled at missing out on 20% of search volume for an exact match keyword set to advanced delivery with what by all accounts should have been a sufficient budget.

What I found was that as I continued to “optimize” the account by adding new keywords, it started to siphon away the impression share that my original keyword was exposed to. The bigger the campaign got, the more confused AdWords became.

Confused is putting it politely, actually. AdWords was straight up dumb in how it chose what keywords to match to searches and how it allocated budget between them.

I’m already a big believer in segmenting campaigns by match type, keeping my exact match keywords in their own campaign separate from broad or phrase. With the impression share issue I was having I decided that this time I would take it a step further.

I separated the exact match brand name keyword into its own campaign with its own budget separate from everything else. I was taking no chances with leaving money on the table for my best keyword during the holidays. When you do this you actually want to move everything else into the new campaign- leave your prize pig alone.

We made the change in October. The results blew my mind. In the previous year during the holidays we saw ROI start to drop as a function of the major increase in holiday traffic. Keep in mind ROI dropped from fan-freaking-tastic to just regular fantastic (official units of measurement).

What we saw as we went into the holidays this year was that our ROI went up at the same time that traffic spiked. When we looked at the holiday season (Nov-Dec) we managed to increase ROI by over 30%. The traffic spike plus the surge in ROI combined for an overall increase in revenue of more than 60%!

This is why there is a picture of money at the top

So do the results translate? Will it work for other brands? Will it work for your brand? We wanted to know.

So we tried it again.

My colleague Timothy Johnson and I looked at one of his client’s accounts. They were seeing year over year decreases in PPC after a huge improvement in organic rankings had reclaimed a bit of the online search pie.

The two channels together were cooperatively outperforming last year’s revenue. Sometimes, though, that explanation just isn’t going to get you off the hook with a client who wants to see improvement in every channel, every year.

We noticed a similar trend that our exact match name wasn’t getting quite the exposure that it could, so we followed suit and gave it its own campaign and a budget it couldn’t possibly spend.

Without adding a single keyword to the account, we increased visits by 11%, revenue by 41%, and transactions by 46%.

I’ll say it again; we didn’t add a single keyword and we didn’t take anything away from SEO. Organic revenue actually grew at the same time.

Do you have any high performing keywords that aren’t getting their fair share of impressions? Your brand name is definitely a good place to start looking, but is by no means your only option.

The main thing I want to get across is that if you have a keyword that’s performing well and it’s important that it shows as often as possible, don’t give AdWords any chance to do otherwise, because it will. Because AdWords is dumb.

Photo Courtesy Of: 401(K) 2013

The post Are You Optimizing Your PPC Campaigns To Death? appeared first on Portent.

The only problem is that Google releases roughly five billion changes to AdWords every day or two (a rough guesstimate on my part). With only so many hours in the day to watch Twitter for new product announcements, it’s really easy for something to go unnoticed or slip through the cracks every now and again.

For instance, I was rather surprised one day when, while doing research for a client, I did a search on Google and found this.

Did you catch that? No?

How about now?

So am I the only one who missed this one?* You can target sites like Facebook, Google+, and Twitter in your Sitelinks Extensions!

*I’m totally not by the way, I asked all of my coworkers and they hadn’t heard either.

Third party sitelinks still need to follow the same rules as normal sitelinks (unique pages, accurate descriptions, no linking to downloads, etc.) but can lead to any of the social media properties listed.

You’re not always going to want to direct users away from your main site, but third party sitelinks can be an extra tool in your PPC arsenal. Using them to gain likes or followers is a start, but what about other possibilities? Running a contest on Facebook? Let people searching for your brand know about it. Hosting a branded hangout? Send users to your Google+ page. Customer support search? How about sending them to your Twitter profile?

Enhanced campaigns also add an extra level of versatility and accountability to the equation. Enhanced sitelinks bring with them better reporting and ad group level targeting. You’ll know exactly how well your third party sitelinks are performing and whether the investment is worth it.

How about you? Did you already know about third party sitelinks? How have you been using them?

The post Google AdWords – Third Party Sitelinks appeared first on Portent.

I hate doing things twice. I also hate doing things by hand. When it comes to PPC reporting, there is nothing quite as cumbersome as recreating reports from scratch month after month.

Thankfully we have the tools available to us to make easy and effective automated reports a cinch. Assuming you have Excel, you’re pretty much set. Rather than duplicate our work every month, we’ll do the work once, and leave ourselves in the best position possible to simply update the data and get on to the analysis.

These principles can apply to any type of reporting, but we’ll be focusing on a Facebook report.

Step 1 – Create your reports

One of the keys to reporting with ease is using reports in their rawest, most standard form. Trimming data adds unnecessary manual labor that our computers can easily do for us.

For our example report we want to give our client an idea of the amount of traffic, Likes, and a couple of specific actions they’re generating on Facebook and how much they’re costing them. Since Facebook’s standard Advertising Performance report only gives you a sum of all actions together and we want data about specific actions, we’re actually going to be pulling two reports. If you want to save yourself some time and can afford to report on actions in general, you can actually avoid pulling a second report.

The first report to pull is the standard Advertising Performance report. We’re going to whip up some year-to-date numbers for the client. Set your time summary to monthly. You can go as deep or as shallow as you want with how you summarize your data – for our purposes, we’ll stick with the campaign level. And don’t worry: your hands won’t be tied if you decide to report by account later on.

Since we want to report on some specific actions, we’ll pull a second report, the Actions by Impression Time report. Same set up as before, monthly with a year-to-date timeline.

Export your reports and we’ll be ready to get started in Excel.

Step 2 – Create tables

The first key to getting our reports set up for easy updating is to put our data in tables. It’s really important to note that you don’t simply use manual filtering or naming ranges here, but an actual table. This is going to be key later on as we add data to our table and it automatically recognizes it as part of the table.

Go ahead and fix the ridiculous way Facebook formats the word “Date” and then make the table. As with everything in Excel, you have two options: I prefer either clicking the “New” button under the Tables ribbon, or simply selecting one of the table styles under the ribbon.

Now that we’ve made our table, let’s name it for good measure. Select a cell inside the table, go to the Tables section of the ribbon and click rename, and rename it something useful to you. I usually go with FBDATA. Remember no spaces and no numbers.

Repeat those last steps for your Actions by Impression Time table (I named this table ACTIONDATA) and we’ll be done making tables. You should end up with something along the lines of this:

Step 3 – Pivot away

We’re going to turn these two tables into three pivot tables that will seamlessly provide our customer with the data he needs.

Go into your FBDATA table, navigate to the Tables section of the ribbon and click “Summarize with Pivot Table.” Your data range should automatically populate, but if it doesn’t just type in FBDATA and you’ll be good to go. Put this pivot table on the report tab.

Before we go any further, make another pivot table using your FBDATA table and put it on the same sheet just to the right of the table. We’ll be back for that one later.

Let’s go to the Report tab and populate our first pivot table. Our client wants to see numbers on Clicks, Impressions, Page Likes, Page Post Likes, Page Post Shares, Spend, CTR, CPC, and CPL. Let’s make it for him.

For our rows we want to summarize first by Date, and secondarily by Campaign. If you want to report at the account level, include Date only. For our values first we’re going to drag Clicks, Impressions and Spend. Don’t forget to format your fields correctly as Sum and give them the correct number type (numbers, currency or percentages).

Now that you have those three, let’s work on the fields that deal with percentages and averages. You can’t get CPC or CTR numbers directly from your table because it will either sum them into a total, or it’s going to find the average of all your CPCs and give you an inaccurate number.

Next, select “Formulas” then “Calculated Fields” under the pivot table section of the ribbon:

Give your new field a name; I tend towards names like “Actual CTR” or something similar. In the formula bar we’ll actually input the fields we want the pivot table to go through.

Continue the process until you’ve got fields for CTR, CPC, and CPL. Even though it’s available here, we’re not going to include numbers on total page likes in this table; we’ll save those figures for the Actions table. Speaking of…

Lets make our next pivot table. Repeat your previous steps and populate the data from your ACTIONDATA table into its pivot table. We’re going to take a little bit of a different approach to building this one. It starts out the same with Campaign and Date as our rows. We are going to place “Action Type” as our column and “Sum of Actions” as our value. Since this gives us more info than we need, we’re going to filter our columns to only include Page Likes, Page Post Likes, and Page Post Shares.

Step 4 – Make it pretty

So that’s great – I gave you two discombobulated pivot tables and I said I was gonna give you a PPC report. We’re almost there.

First things first: let’s go back to that second pivot table you made from FBDATA. Select “Date” as your rows and “Clicks” and “Page Likes” as your values.

Click any cell inside the pivot table, go to the chart portion of the ribbon and select a column chart. You just created a chart that will automatically update stats as your pivot table updates. Move the chart onto the “Reports” tab and let’s start beautifying this lovely pile of pivot. You should be looking at something like this:

First, let’s make sure our two tables match up line for line. Do you have months with no action data? You may have to do some one-time manual labor. If you find you have any missing months, you’ll need to go to your ACTIONDATA table and input columns for each action you want to track for any month that is missing.

Make sure you input your date in the same format as the rest or you’ll end up with an extra entry. Copy and paste if you can. Add one column for each of your tracked actions (in this case three) and put as the total number of actions. This will give your pivot table something to latch on to. After you’re done, your pivot tables should match up exactly. That’s going to be important in a minute.

In my opinion, pivot tables look a little hokey in their native form. The nice thing is that there are a ton of options for sprucing them up. Choose a style that looks clean and professional and if applicable fits with the rest of your reporting. Lets also get rid of some of the extraneous formatting. We don’t want totals for columns, we don’t want triangles, and we don’t want headers.

After you’ve done that, take some time to go through your pivot table fields and rename them. I tend to replace “Sum of” with “Total” or “Average.” Don’t forget to do this on your chart’s pivot table too. I also decided that since my client only has one campaign, it would be redundant to include the campaign name and date. So I’m going to remove “Campaign” from my rows. So fresh and so clean.

This is purely a personal preference but on my chart I like to track page likes as a line rather than columns, and I like to track it on a secondary axis. I think it looks pretty so I’m gonna do it.

If you also want to do this, it’s pretty simple. I start by selecting “Total Likes” in the legend and then selecting the line chart type. Then I select the line, right click, and choose “Format Data Series.” Under the axis menu pick the option for secondary axis. Looking good.

It’s totally a personal preference thing for me, but I like having my chart up at the top with the client info; it gives them a clear picture right away. If you need to move your pivot table to make room, it’s really easy. Just highlight everything (including the blank filter bar at the top), and drag it with the hand cursor down to where you want it. You can also use the “Move” command on the pivot table section of the ribbon.

You’re so close to being done. Line up your two pivot tables so that the rows match and simply hide the space between them and the Date and Campaign names on your second pivot table.

How’s about that? You just made a year-to-date report with two sheets of data.

Hide those data tabs and send it off.

Step 5 – Update update update

Now this would kind of be a waste if this were a one-off report. But the beauty is that you just did the leg work for (roughly) the rest of your life.

Next month when reporting time comes again, pull those same reports. Copy and paste the data into your two tables (update the actions if you need). Now go to one of your pivot tables, go into the pivot table section of the ribbon, click “Refresh” and “Refresh All” and you’re done.

Seriously.

It probably took you longer to read that than it will take you to do it.

Enjoy.

Strange there seems to be a 30 year gap in my data…

The post An Easy Way to Automate Your Facebook Reporting Using Pivot Tables appeared first on Portent.