Qmd 1903 wast_googad

Are You
Wasting Money
on Google Ads?
A Practical Guide to Eliminate
Wasted Spend and Maximize ROAS
on Google Ads in 5 Simple Steps

2ARE YOU WASTING MONEY ON GOOGLE ADS?
What’s Inside
Introduction...........................................................................................................................3
Success Story: How Windstar Saved Nearly 1 Million on Ad Spend...................4
Discovery Checklist............................................................................................................5
Step 1: Keyword Level Efficiency Analysis..................................................................7
Industry Benchmarks ...................................................................................................7
Analysis Process............................................................................................................8
Analyzing Results......................................................................................................... 14
Step 2: Percentage of Keywords without Clicks Analysis....................................15
Analysis Process.......................................................................................................... 15
Analyzing Results......................................................................................................... 16
Tackling the Challenges of Leveraging Bid Adjustments.................................. 16
Step 3: Location Efficiency Analysis...........................................................................18
Industry Benchmarks.................................................................................................. 18
Analysis Process.......................................................................................................... 18
Step 4: Hour of Day and Day of Week Efficiency Analysis................................. 27
Analysis Process..........................................................................................................27
Step 5: Device Efficiency Analysis...............................................................................41
Insights from your Analysis....................................................................................... 42
QuanticMind Helps You Eliminate Wasted Ad Spend..........................................43
How does QuanticMind Help You to Maximize PPC ROI?............................... 43
Next Steps?................................................................................................................... 44
Request a Demo.......................................................................................................... 44

Introduction
Search advertising is the largest expense for most digital advertisers,
yet many are uncertain they’re spending efficiently. Google Ads
(formerly Google Adwords) and Bing Ads have evolved dramatically
over the past several years, developing more features that enable
advertisers to make their ad targeting more precise and their keyword
bids more efficient.
This is great news in concept, but the practical complexities of this
opportunity can be overwhelming. Most advertisers lack the tools
needed to take advantage of the new Google Ads features. Say, for
example, you have a simple program with 5,000 keywords and 10
retargeting lists. This program would yield 5.2 billion potential bid
variations to calculate on a daily basis. (5000 Keywords * 10 Audiences
* 24 Hours * 7 Days * 210 Metro Areas * 3 Device Types = 5.2 Billion)
If you bid effectively, you can achieve extreme precision — eliminating
wasted advertising spend and producing huge returns. In fact, with the
right AI-powered bid-management tool, advertisers are able to save
millions of dollars a year.
So how can you tell if you are best leveraging the tools available to get
to the right bid for each scenario? This step-by-step guide will help you
quantify the amount of opportunity you have to improve your returns by
pulling these levers via five discrete analyses to run on your program:
• Step 1: Keyword Level Efficiency Analysis
• Step 2: Percentage of Keywords without Clicks Analysis
• Step 3: Location Efficiency Analysis
• Step 4: Hour of Day and Day of Week Efficiency Analysis
• Step 5: Device Efficiency Analysis
In short, it will help you determine how much money you’re wasting on
Google Ads annually.

“Why the
Partnership with
QuanticMind will
‘Last a Lifetime’
Success Story: How Windstar Saved
Nearly 1 Million on Ad Spend
Challenge
You might not think a beloved, gold-standard cruise line would need to
sell itself, but it’s a crowded world. Windstar Cruises, which boasts six
different ships across 300 ports and 80 countries, knew that while its
customer experience was top notch, it’s market share could improve.
The marketing department also had a sneaking suspicion that they
were wasting money by underutilizing the most advanced technologies
available today.
Victor Hernandez, SEM Director at Windstar took a hard look at their
approach and realized he needed to make a change.
Solution
After using Search Engine Marketing agencies and other search
marketing tools, Victor selected QuanticMind due to its AI-powered
bid-management solution. Leveraging large data sets, the QuanticMind
platform is able to gather specific information and generate insights
— effectively learning over time how to optimize bids to reduce
conversions, reduce CPC, and increase overall sales. QuanticMind’s
platform can react quickly in real time based upon data and adjust bids
up to four or five times a day.
Results
According to Hernandez, Windstar “ended up saving $700,000” and
increased their “goal conversions by 16 percent year-over-year.” That’s a
lot for one streamlined, cost-effective platform to provide.
“We’ve ended up saving $700,000 roughly and increasing our
goal conversions by 16 percent year-over-year.
To find out how Windstar Cruises leveraged QuanticMind to save
money, watch the video testimonial now!
Victor Hernandez,
SEM Director

Discovery Checklist
But before you dive into this exercise, we recommend you answer the
bid optimization questions in the checklist below to get started:
☐☐ Do I understand the impact each keyword has on my deep funnel
conversions? (Think leads, LTV, Lead Score, Phone Call Conversions,
Revenue, Profit, Store Visits, Signed Contracts, Converted Pilots)
☐☐ Can I bid on each keyword based on its ability to drive those results,
or am I stuck with grouping keywords together and dealing with
averages?
☐☐ Can I bid on keywords that have little or no data? What about
keywords with infrequent, high value conversions?
☐☐ Location: Am I making full use of location based bidding? Am I
bidding the right amount given which city the person is searching
from? Do I account for daily trends within each city?
☐☐ Day Parting: Am I bidding the right amount for the time-of-day/day-
of-week combination? Do I have a scalable way to bid differently
based on Day of Week performance? For example, if my conversion
rates are better on Thursday afternoon than on Wednesday
afternoon, am I using that information to my advantage?
☐☐ Device: Am I targeting specific devices or bidding differentially
based on Device? Do I know how much device matters?
☐☐ Audiences: Do I understand my audiences, and do I have a
scalable way to bid the right amount for each audience based on
performance? Am I updating my audience targets frequently based
on Day of Week or seasonal trends?

If you can only answer yes to two or three of these questions, then
you are a very typical advertiser. Most advertisers, including smart
advertisers running sophisticated programs, aren’t fully leveraging the
majority of these capabilities. They simply lack the technology to control
this complex set of options.
Now that you’ve answered these questions, you’re ready to roll up your
sleeves and find out how your program is doing.
For this, you will need:
• Approximately 45 minutes of free time without distractions
• Read-only access to your Adwords account(s)
• Three months’ worth of Conversion or Revenue data in your Adwords
account(s)
• The ability to run pivot tables in Microsoft Excel (instructions are
provided in this article).
In the next analysis, we’ll take you through each step to evaluate your
Google Ads spending. No matter how basic or complex your PPC
program is, you’ll have all the tools you need to work through and
discover your wasted ad spend. In our first analysis, we’ll take a look at
keyword level efficiency.

Step 1: Keyword Level Efficiency
Analysis
BRIEF DESCRIPTION: For our first analysis, we’ll reveal the percentage of
spend for non-converting keywords over a three-month period.
Industry Benchmarks
First you need to assess how your program is performing. Determining
overall performance can be quite difficult, as it varies dramatically based
on conversion type. Here are some trends and recommendations we
make based on business type, industry and other factors:
• B2B companies with high value, low volume conversions: it’s
common to see 60% of spend applied to keywords without
conversions.
• B2C retail companies with low value, high volume conversions:
It’s common to see 15-30% of spend applied to keywords without
conversions. For super high volume/low value conversions, we
recommend using a ROAS threshold instead of conversions. For
example: If 2X ROAS is your profitability threshold, then run this
analysis for percentage of spend applied to keywords that are below
2X ROAS instead of percentage of spend applied to keywords
without conversions.
• Automotive companies where conversions are a Vehicle Description
Page view, Request for Quote, Dealer Locator, Download a
Brochure, Build and Price, etc. It is common to see an extremely low
percentage of spend applied to keywords without conversions. In
such cases, we recommend picking a specific conversion metric that
you wish to improve (such as Request a Quote only).
• Travel companies: We recommend looking at Bookings as a
conversion. Some travel customers have hundreds of millions

of keywords but others only several thousand, depending on
the business model. If you have hundreds of millions, then we
recommend applying filters and running this analysis on your top
100K keywords.
• Financial companies where conversions are completed applications:
We tend to see that the majority of spend is on head terms, and
a very low percentage of spend is applied to keywords without
conversions. In this case, we recommend looking at the percentage
of long tail keywords with clicks. Non-brand head terms are
expensive in this space, so the more you can extract value from the
long tail, the better.
• Lead generation companies that provide leads to local contractors:
Performance numbers vary dramatically depending on the type of
conversion. For initial form submission you should expect to see
less than 10% of spend on keywords without conversions. You can
improve the quality of leads by feeding deeper funnel conversions
(such as accepted leads or booked contractors) into your bidding
optimization program.
• Publishers who make most of their revenue from Adsense or from
running display ads: In this case conversions are typically extremely
high volume/low value. So we recommend using a ROAS threshold
instead of Conversions. For example: if 2X ROAS is your profitability
threshold, then run this analysis for percentage of spend applied to
keywords that are above or below 2X ROAS.
Analysis Process
Once you’ve considered a benchmark for your program, you’re ready to
start the analysis process:
1. Determine Accounts and Conversion Fields
a. Determine Account: It is easiest to run this analysis on one
account. If you have several accounts, then you could choose the

largest account, or the account that best represents the rest of
your program. Click into that account.
b. Determine Conversion Field: Navigate to your Conversions Page
in Adwords (New Adwords Interface — Wrench » Measurement
» Conversions). Determine which is the most meaningful for your
analysis. I typically use “All Conversions” unless the account has
a lot of high funnel conversions like product page views or a help
video included.
2. Prepare and Download the Data
a. Navigate to the keywords tab within the account you have chosen
to analyze.
b. Apply a filter: Campaign Type: Search Network Only.
Note: If your report is longer than 1 million rows, you may want to
add additional filters (such as Keyword Status: Eligible) because
you are going to be downloading this to Excel.
c. Change the Date Range in the top right corner to reflect the last
90 days.
d. Add Columns: Keyword, Impressions, Clicks, Cost, Match Type.
Include whichever conversion column you decide to utilize. You

may also want to include custom dimensions (such as brand/non-
brand) if you want to see your results broken down as such.
e. Download the report in Excel.
3. Excel Work
a. Remove the summary rows at the top and bottom. Here’s how:

b. Add a column at the end and name it “Clicks?” Then add another
column at the end and name it “Conversions?” It should look like
this:
c. In the “Clicks” column, type the formula: =IF(ClicksCell, “Has
Clicks”, “No Clicks”)

d. Extend this formula to the entire column
e. In the “Conversions” Column, type the formula:
=IF(ConversionsCell,”Has Conversions”, “No Conversions”)
Note: If you are using a ROAS threshold instead of Conversions,
then replace “Conversions” with “ROAS Threshold.” Then create
an ROAS column (Revenue/Cost). Use this formula to populate the
ROAS Threshold column: =IF(ROASCell>[insert ROAS profitability
Value],”ROAS GT Threshold”, “ROAS LT Threshold”). In this
example, the ROAS profitability threshold is 500%, so we used this
formula: =IF(ROASCell>5,”Above 5X ROAS,” “Below 5X ROAS”)
f. Extend the formula to the entire column

g. Select all data and create a Pivot Table (Click “OK” on the next
dialog)
i. Rows: “Conversions?” (or optionally use “ROAS Threshold”
instead)
ii. Columns: Match Type, brand, non-brand, etc. (optional—
depending on which dimensions you want results broken out
by)
iii. Values: Cost (Sum of)
h. Calculate the % of non-converted spend (spend with no
conversions/total spend) for each column (broad, exact, total)

Analyzing Results
A healthy non-converted spend % is usually somewhere below 20%.
Too low a percentage means too little keyword discovery. Too high a
percentage means waste. Please see the industry benchmarks for your
specific vertical. The account in the example screenshot has 6.3%. That
is probably too low, meaning that efficiency is strong, but that there
is an opportunity to explore the long tail for more volume. The next
analysis will help us confirm that.
100%0%
Healthy
non-converted
spend
(below 20%)
Too little
keyword
discovery
PERCENTAGE
EFFECTIVENESS

Step 2: Percentage of Keywords
without Clicks Analysis
BRIEF DESCRIPTION: Now we’re going to determine the percentage of
keywords that don’t have clicks. This will help reveal the opportunity for
better exploration in the long tail. If more than 30% of your keywords
have not had clicks in the last three months, then there’s a lot of
opportunity.
Analysis Process
Now you’ve already done half the work because you’re going to start
from the pivot table you created in Analysis 1. Adjust the pivot table as
follows:
1. Rows: Clicks?
2. Columns: Match Type, brand, non-brand, etc (optional — depending
on which dimensions you want results broken out by)
3. Values: Keywords (count of)
4. Now compare the number of keywords that have clicks to the
number of keywords that do not.

Analyzing Results
A healthy percentage of keywords without clicks is usually somewhere
below 30%, though it is extremely common to see numbers higher than
50%. Too high a percentage means you might not be bidding enough
for the long tail. This is usually caused by lack of data to determine
how much to bid. QuanticMind solves this problem by using Natural
Language Processing (NLP) to bid intelligently on long tail keywords by
automatically borrowing data from semantically similar head terms.
Tackling the Challenges of Leveraging Bid Adjustments
The next three analyses assess the opportunity to better leverage bid
adjustments for Location, Hour of Day, Day of Week and Device. These
levers provide powerful targeting capabilities. So what’s the problem
with that?
1. Bid Adjustments provide an overwhelming number of combinations
to address, much like a Rubik’s cube with only three inputs. Achieving
peak performance with these tools is a complex problem.
2. It’s difficult to adjust modifiers optimally for each individual
keyword without adversely affecting the rest of the campaign.
That’s because Bid Adjustments are set at different levels (e.g.
Campaign level for Location, Ad Group level for Device).
3. It is hard to keep up. In an ideal world, bid adjustments would
change each day based on historical performance, seasonality
trends, and the competitive bid landscape. Most advertisers have
dabbled in adjusting bids on a daily basis, but have found it not
worth the manual effort.
4. Bid Adjustments stack, combining to affect the final bid price. We
have seen several scenarios where bid adjustments are calculated in
separate silos for Hour of Day, Location, and Device, resulting in run-
away final bid amounts. This is a known problem, but the alternative
(which is to calculate all bid adjustments together, considering how

they each influence each other) is too complex. QuanticMind uses
Machine Learning to solve this challenge.
It is no surprise to see inefficiencies for each bid adjustment type given
these challenges. But the problem is not with your bidding practices.
Instead, it usually represents a lack of technology.
With all that in mind, here is the industry benchmark that we calculated.
We analyzed: $200M Ad Spend, 310M Keywords, 85K Campaigns, 12
months, across 11 verticals, managed by first generation platforms to
determine benchmarks for our study. We aggregated all the accounts
and followed the same methodology described in the next three
analysis. Here are the results:
Google Ads has provided a solution with Smart Bidding, but many
advertisers hesitate to use it because of lack of visibility into bid change
history, corporate privacy policies that prevent sending Revenue data
to Google, and the desire to have a neutral third party drive bidding
decisions.
In the next three analyses we’ll show you how to calculate wasted
spend and missed opportunities from these same bid adjustments in
Adwords.
By State
Without Data Science, Poor Investments Are Made
Wasted Spend and Missed Opportunity
17.1%
By City (within CA)
18.6%
By Device
9.1%
By Day of Week
& Time of Day
6.6%

Step 3: Location Efficiency Analysis
BRIEF DESCRIPTION: This analysis quantifies the opportunity to improve
performance by fully leveraging Location Bid Adjustments. Values are
shown as a total cost impact that is derived from the deviation from
average CPA (spend too high or spend too low) for each location
segment.
Industry Benchmarks
For nationwide campaigns, this is consistent regardless of industry. For
state targeted campaigns (common in finance), we ignore state level
and look only at city level data within each state. Averages are 17.1% by
state, and 18.6% by city.
Analysis Process
a. Determine Account: It’s easiest to run this analysis on one
your program. Click in to that account.
analysis. It’s best to use “All Conversions” unless the account has
video included.

a. Navigate to Reports (chart icon on top right » Reporting » Reports)
b. Click New Report » Table

c. Add Rows: Region, City (Note: DMA has been deprecated.)
d. Add these columns:
i. Impressions
ii. Clicks
iii. Cost
iv. Conversions
e. Filter by Campaign Type:
i. Search Only
ii. Search Network with Display Select
f. Change the Date Range in the top right corner to reflect the last
90 days.
g. Download CSV

3. Excel Work
a. Create a new column for CPA
b. Set the value to be this formula (=Cost/Conversions)
c. To help visualize the deviations from average CPA, highlight
all the data cells in your new Conversions column and apply
conditional formatting (Choose the first of the color scales).

While the cells are still highlighted, complete the following steps to
normalize the heat map to percentiles instead of values.
1. Click on Conditional Formatting » Manage Rules…
2. Click Edit Rule

3. Change the Type dropdown to Percentile for both the Minimum and
the Maximum columns.
4. Leave the percentile values at the defaults (10, 50, 90)
5. Get the Average CPA: Divide the Total Cost by the Total Conversions
to get this. Then note the Average CPA.

6. Create a new column called “Deviation” for deviation from average
CPA. Use this formula for the Deviation column: Deviation = (CPA/
[insert average cpa value]) -1
Change the formatting to display the Deviation Values as a percentage.
Your spreadsheet should now look like this:

7. Finally, calculate the cost impact of deviation.
a. Create a new column for the Cost Impact of Deviation.
b. Populate the top cell with the following formula: “=abs(Deviation
from average CPA for that segment * Cost for that segment)”
c. This will take the absolute value of the average deviation, and
multiply it by the cost so that you can see the Cost Impact. The
Cost Impact represents the amount of spend too high or too low
for each segment based on your CPA targets.
Note: This can be done with ROAS as well if that is your target.
d. Extend the formula to the adjacent cells to fill in the rest of the
column.
e. Add up the total cost impact for all the segments to get the total
cost impact across all segments.

f. Divide the total cost impact by the number of months in the
analysis. This will give you the Monthly Cost Impact that effective
use of automated modifiers can have.
In the screenshot example, there is an opportunity to improve CPA-
based performance by 20% with the proper use of city based bid
adjustments. This is commonly missed because calculating bid
adjustments for every city every day can be overwhelming — even with
software.

Step 4: Hour of Day and Day of
Week Efficiency Analysis
BRIEF DESCRIPTION: This analysis quantifies the opportunity to improve
performance by fully leveraging Hour of Day and Day of Week Bid
Adjustments. Values are shown as a total cost impact that is derived
from the deviation from average CPA (spend too high or spend too low)
for each Hour of Day and Day of Week segment.
Note: One of the challenges with Hour of Day modifiers is determining
the Hour of Day segments definitions. Adwords allows up to six Hour of
Day segments with 15-minute increments. So you could have an “Early
Morning” segment of 5:45 am to 9:30 am, a “Late Morning” segment of
9:30 am to noon, and so on. Calculating the ideal Hour of Day segments
is not addressed in this guide. Instead we treat each hour separately to
get a sense for the opportunity. QuanticMind solves this complexity by
automating the creation of Hour of Day segments and calculating bid
adjustments for each segment each day, based on your business targets.
Analysis Process
a. Determine Account: It is easiest to run this analysis on one
your program. Click in to that account.
analysis. I typically use “All Conversions” unless the account has
video included.

a. Navigate to Reports (chart icon on top right » Reporting » Reports)
b. Click New Report » Table
c. Add Rows: Hour of Day, Day of Week
Note: If Hour of Day is grayed out, then you may need to
choose a different conversion event. Conversion events that
are not loaded in real time, such as offline conversions, are not
associated with an Hour of Day.

d. Add the following columns: Impressions, Clicks, Cost,
Conversions
e. Filter by Campaign Type: Search Only, Search Network with
Display Select
f. Change the Date Range in the top right corner to reflect the last
90 days.
g. Download excel

3. Excel Work
a. Create a new column for CPA
b. Set the value to be this formula (=Cost/Conversions)
c. Don’t worry about formatting this one just yet. The Hour of Day
and Day of Week segments will be better illustrated in a grid
layout — which we will do shortly.
d. Get the Average CPA as you did in the previous analysis.
e. Create a new column called “Deviation” for deviation from
average CPA. Use this formula for the Deviation column:
Deviation = (CPA/[insert average cpa value]) -1

Change the formatting to display the Deviation Values as a percentage.
Your spreadsheet should now look like this.

f. Finally, Calculate the Cost Impact of Deviation
i. Create a new column for the Cost Impact of Deviation.
Then populate the top cell with the following formula:
“=abs(Deviation from average CPA for that segment * Cost
for that segment).” This will take the absolute value of the
average deviation, and multiply it by the cost so that you can
see the Cost Impact. The Cost Impact represents the amount
of spend too high or too low for each segment based on your
CPA targets.
Note: This can be done with ROAS as well if that is your target.
ii. Extend the formula to the adjacent cells to fill in the rest of the
column. Add up the total cost impact for all the segments to
get the total cost impact across all segments.

iii. Divide the total cost impact by the number of months in the
analysis. This will give you the Monthly Cost Impact that
automated modifiers can have.
In the screenshot example, there is an opportunity to improve CPA-
based performance by 11% with the proper usage of Ad Scheduled
Modifiers (Hour of Day and Day of Week based bid adjustments).

Now let’s create a better way to visualize the results. The following
steps will guide you through the creation of several tables to get a nice
picture of how your Impressions, Clicks, Conversions, and CPA play out
for each of your Hour of Day/Day of Week segments.
If you follow this process you will have a set of tables that look like this:
1. Highlight all, Create pivot table
2. Table building steps (You will repeat this once for each metric:
Impressions, Cost, Clicks, Conversions, CPA, Deviation. As
mentioned earlier, you can skip to the CPA table to save time.)
a. Create Impressions Table
i. Add to Rows: Day of Week
ii. Add to Columns: Hour of Day
iii. Add to Values: Impressions (sum of)
iv. Copy the Impression data and paste it into a new set of cells
below the table

b. Create the Cost Table
i. Remove Impressions from the existing pivot table. Replace
with Cost.

ii. Copy the new Cost data and paste it into a new set of cells
below the Impressions table.
c. Repeat for the rest of the metrics (Clicks, Conversions, CPA,
Deviation).

At this point you should have a set of unformatted data tables for
each metric. Now, we will apply conditional formatting to highlight
the daily/hourly trends and areas of opportunity.
i. Highlight all the data cells in your Impressions table and apply
conditional formatting (Choose the first of the color scales)
ii. While the cells are still highlighted, complete the following
steps to normalize the heat map to percentiles instead of
values (this will make the Impressions heat map you’re
creating match up better with the Clicks, Conversions, Cost
and CPA heat maps that you will make next.)
1. Click on Conditional Formatting » Manage Rules…

2. Click Edit Rule
3. Change the Type dropdown to Percentile for both the
Minimum and the Maximum columns.
4. Leave the percentile values at the defaults (10, 50, 90)

Use the Format Painter to apply the same Conditional Formatting to the
rest of the tables.
Finally, set the correct number formatting for each of the tables (CPA’s
formatted as $, Deviation from average as %).

At this point, you should have something that looks like this:
Assume that the pattern for your data is pretty predictable for the
Impressions, Cost, Clicks, and Conversions. Is it also predictable for
CPA or is it scattered like it is in the example screenshot? We normally
find the scattered results for CPA as well as ROAS. The reason for this
is that most software does not optimize key metrics (like CPA or ROAS)
for each Hour of Day and Day of Week. It tends to be too complex to do
that while also optimizing for City and Device.

Step 5: Device Efficiency Analysis
If you do not have a deliberate device strategy in place (such as device
targeted campaigns with separate goals), then you could repeat the
Hour of Day analysis, swapping Hour of Day for Device. Your results
might look something like this:

In this example, there is a pretty clear pattern between Mobile, Desktop
and Tablet, however the pattern does not hold up each day of the week.
If the pattern holds throughout the week, then your device strategies
are probably working for you. But if the pattern falters (as in this case)
then there may be opportunity to automate Device bid adjustments
each day.
Insights from your Analysis
So now you have a few efficiency metrics to help determine the
opportunity for optimization. Are they big enough to trigger change?
As you decide that, keep in mind that the opportunity is bigger than
this analysis may look. This analysis is done at the Cost level, and if
you want to understand how this affects your bottom line, then multiply
cost impact by ROAS to understand the overall impact on business. For
example, if your total cost impact is $10K/month and your typical ROAS
achieved is 3X, then the impact on your bottom line is $30k/month.
We hope this step-by-step guide has helped you uncover at least
a few pockets of opportunity for optimization. If you need help
executing on this, then read on.

QuanticMind Helps You
Eliminate Wasted Ad Spend
In this guide, we’ve walked you through how to determine if you’re
wasting ad spend on Google Ads, as well how to determine new
opportunities to boost ROI and truly optimize your campaigns to their
full potential. Now that you know you’re wasting money on Google Ads,
the next step is to consider tools such at QuanticMind, which can help
you maximize ROAS.
How does QuanticMind Help You to Maximize PPC ROI?
Modifier Complexity: QuanticMind breaks out each keyword into
distinct combinations of Keyword x Location x Hour of Day x Device x
Audience (Audiences coming soon). Then we determine the ideal CPC
for each of these combinations. Finally, we use Machine Learning to
back into each modifier to get the entire program as close to the ideal
CPC as possible.
Hour of Day segments: QuanticMind solves the complexity by
automating the creation of Hour of Day segments and automatically
calculating bid adjustments for each segment each day, based on your
business targets.
Long Tail Data Scarcity: QuanticMind uses Natural Language
Processing (NLP) to bid intelligently on long tail keywords by
automatically borrowing data from semantically similar head terms. This
provides significant lift in terms of clicks and conversions from the long
tail without the need for costly trial and error.
Location Data Scarcity for small cities: Similar to our practice of utilizing
NLP for the long tail, QuanticMind compares city-level demographic points
to each other to allow small cities to borrow data from demographically
similar large cities. This provides lift by applying intelligent Location bid
adjustments to cities that do not have sufficient data to support it.
“Predictive
analytics
allow us to
uncover hidden
opportunities
while eliminating
hidden waste.

Request a Demo
Already convinced QuanticMind can help you become a PPC rockstar? Then why not watch a live demo
of the QuanticMind AI-powered bid management platform to see how you can automate optimization for
specific keywords and target the highest quality leads using data from every stage of the funnel.
Request a Demo »
Keyword Inefficiency: QuanticMind has the processing power to
address each keyword separately, applying your business goals at the
most granular level and generating incremental lift.
In short, if you want to improve volume, quantity, and efficiency of your
PPC program, QuanticMind is the perfect solution. By using data science,
QuanticMind can collect every data point about a click and identify the
most profitable price to acquire customers. Use it to automate advanced
campaign modifiers such as geo, device and time of day.
AI-powered bid management makes it possible to derive insights and
take actions to improve ROI/ROAS faster than a team of professional
data scientists. QuanticMind can handle an unlimited number of data,
keywords and publishers from one account, making it a one-stop
solution for staying ahead of the PPC competition.
Next Steps?
Now that you have these numbers, you can decide if it’s worth the effort to
make improvements. We want to help! Feel free to contact QuanticMind »
Bring us the results of your analysis and we can propose a
solution to reach peak efficiency.
Or ask us to conduct the analysis on your behalf. We love this
stuff! See for yourself how data science and machine learning
can optimize your ad spend and maximize ROAS.

About QuanticMind
QuanticMind, the Platform for Smarter Advertising, is the pioneer
of predictive management software for digital marketing channels,
including paid search and social. By reinventing ad management point
solutions through machine learning, distributed cloud computing,
and in-memory processing, QuanticMind delivers the most intelligent,
scalable, and fastest platform for maximizing digital performance for
enterprises. A global community of data-driven marketers relies on
QuanticMind’s data science-powered platform to anticipate and execute
the best and most granular investments across their paid channels.
Connect with QuanticMind
We’d love to connect with you on social media.
About the Authors
Seth Jennings, Director of Sales Engineering at QuanticMind
Lynn Langmade, Sr. Director of Marketing Content & Communications
at QuanticMind, @llangmade
Request more Information
www.quanticmind.com
(650) 362-8085
  

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