of shoppers’ wish lists. An estimated 10 million Amazon Echoes are currently in people’s homes. The era of voice search is within reach for the average consumer and not just something we watch in awe during the latest high-tech film. But...how will retailers track the consumer’s path to purchase? How would retailers “show” ads on these smart devices?
As some of you may know, Google AdWords works through statistical computing. The functions within AdWords (such as bid algorithms, auction management, etc.) work on the basis of statistical probabilistic formula. Hence, PPC marketers need to embrace statistics as equally as they connect with their digital marketing tools.
That’s where R comes in handy. What is R? It’s a programming language designed specifically for statistical computing. It empowers both descriptive and inferential statistics, while enabling lots of graphical techniques. Best of all, it’s an open source software that’s free to use and hence, has become one of the most favorite languages of statisticians.
3 Reasons We Should Consider R for AdWords Analyses
1. R enables sophisticated statistical analyses: Imagine a situation where you have to do multivariate testing within AdWords. While AdWords enables the test environment, R provides you with all analytical methods.
2. Visualization capabilities of R are amazing: The graphical abilities of R are unparalleled. From visualizing data points in a map to normal bar charts, everything is available in R. This helps in visualizing the account and campaign performance from multiple perspectives.
3. A vast community of statistical programmers: Since R is open source, there’s a vastly incalculable community of programmers actively contributing to R. You’ll see numerous advanced statistical packages in R and realize that we just need to plug n’ play to arrive at astonishing insights.
Baby Steps in R & AdWords
Once R console is set up, you’re ready to write your first AdWords statistical program. You should be creating Google AdWords API credentials to setup the authentication route from R to AdWords. If you’re feeling a little lost, contact our team at email@example.com and we’ll help you out!
Once inside the console, try running the following script to see how your first statistical program works. This program captures the campaign’s cost metrics and plots them in a box plot.
The Secret Formula To Rule Them All
#invokes the AdWords package within R library(RAdwords) #the below command will prompt for the API credentials google_auth <- doAuth(save = T) #query to capture the campaign performance report between two dates body <- statement(select=c('CampaignName','Impressions','Clicks','Cost','Ctr','SearchBudgetLostImpressionShare','SearchRankLostImpressionShare','Conversions','ConversionValue'),report="CAMPAIGN_PERFORMANCE_REPORT",start="2017-01-01",end="2017-01-25") #runs the query in the respective account adWordsData <- getData(clientCustomerId = 'XXX-XXX-XXXX',google_auth = google_auth, statement=body) #creates a boxplot for the cost boxplot(adWordsData$Cost)
NetElixir projected a moderate YoY growth of 10.5% and 11% during the holiday season. In comparison, eMarketer forecasted a 17% increase and Deloitte predicted a 17 to 19% growth.
Our conservative estimate was due to three key factors, including:
Earlier than usual purchasing of holiday gifts, driven by Prime Day.
Ever wonder how websites seem to just know you and your interests?
It’s called real-time personalization and it’s changing the way potential customers are targeted. This process allows marketers to tailor the presentation of a website’s content to match a specific user’s instructions or preferences. These changes happen in just milliseconds and they’re ultimately about user engagement.
As families and friends were enjoying a feast of Thanksgiving Day turkey, creamy mashed potatoes, cranberry-orange relish, classic stuffing, and more tasty treats, our team was out there reviewing data on consumer behavior throughout desktop and mobile. From the anxiety-fueled claustrophobic shopping fever of Black Friday to the screen-centered focus of Cyber Monday deals, we were there in the trenches collecting valuable data.
This holiday season, e-marketers have a lot on their hands when it comes to preparing for Q4. That’s why our team at NetElixir is sharing our secret to success with a helpful checklist for better performance and revenue into the new year. Continue reading to find out more!
How You Can Prepare at the Account Level:
Now that Thanksgiving dinner is over, Black Friday crowds are gone, and Cyber Monday deals have ended, here are some interesting stats to munch upon. Note that we have considered data from Adobe’s cmo.com as well as the data mined by NetElixir’s proprietary tool, LXRInsights.
Our holiday projections have been featured in Internet Retailer, BizReport, eMarketer, MediaPost, and more! Find out what all the buzz is about at our webinar, 2016 Holiday Weekend: By the Numbers, on Friday, December 2nd from 2 to 2:30 p.m.
We’re excited to announce that we’ll be conducting primary research on a quarterly basis to uncover consumer insights! Our very first consumer survey sought to discover the unique behavior of customers in regards to holiday shopping. Our team uncovered surprising insights into who, what, where, when, why, and how consumers are shopping this season. We wanted to share some of these insights with you.
Our recent webinar, Holiday Shopping Behavior: What to Expect from Your Customers, utilized data from our Google Consumer Survey to gain valuable insights on how people search and buy products. Our Director of Analytics, Don Rodriguez, walked us through some of our insights on holiday shopping behavior. Continue reading to find out four more insights!
Our recent webinar, Holiday Shopping Behavior: What to Expect from Your Customers, utilized data from our Google Consumer Survey to gain valuable insights on how people search and buy products. Our Director of Analytics, Don Rodriguez, walked us through the process starting with our methodology.