Using Targeted Segmentation

How to Make Your PPC Campaigns More Efficient

Agenda

Optimise Bids Through Segmentation

Differentiated Estimates of Sales Results

Split Match Types & Ads

Time of DayRegionsSemantic ClustersWeekdays

Optimise Bids via Segmentation

The electronics retail segment registers high performance levels at the beginning of the week in particular.

From Monday to Wednesday, conversion rates are above average by up to 19%.

Keywords bids are often only based on the weekly average.

Differentiate Conversion Rates by Weekdays

0.00% 0.50% 1.00% 1.50%

Mo

TueWe

ThuFriSatSun

Scheduling bids by weekdays results in higher keyword positions from Monday to Wednesday. The number of clicks increases on days that register high conversion rates, while the cost-turnover ratio remains constant.

Scheduling Boosts Revenues by 8%

0 € 200,000 € 400,000 € 600,000 € €(100,000) €- €100,000

Revenues Change in revenuesMoTueWe

ThuFriSatSun

By using the dimensions tab, you can evaluate the segments “Day of the week”, “Hour of the day”, “Regions” etc.

AdWords: Dimensions Tab

Conversion Rates and Time of Day

22 - 2420 - 2218 - 2016 - 1814 - 1612 - 1410 - 128 - 106 - 84 - 62 - 40 - 2

0.0% 0.5% 1.0% 1.5% 2.0%

In this B2B example, conversion rates peak before lunch time.

Apparently, investment decisions are rarely made after 4pm.

Other examples: In the context of B2C retail, conversion rates peak after 4pm and during lunch time.

+ 5% Sales, Cost-Turnover Ratio Unchanged

The more conversion rates fluctuate during high-traffic hours, the higher your profits will be.

If your cost-turnover ratio is allowed to increase slightly, you will find that scheduling is more effective in generating sales than having your ads placed at generally higher positions.

22 - 2420 - 2218 - 2016 - 1814 - 1612 - 1410 - 128 - 106 - 84 - 62 - 40 - 2

-100,000 € 400,000 €

Change in sales

Combining “Weekday” and “Time of Day”

On average, conversion rates decline rapidly after 4pm. The only exception is Tuesday.

Combining “Weekday” and “Time of Day” will allow you to take these exceptions into account.

Mon Tue Wed Thu Fri Sat Sun0 to 4 0.6% 0.7% 0.7% 0.7% 0.7% 0.6% 0.5%4 to 8 2.1% 1.9% 1.7% 1.9% 2.1% 0.8% 0.7%

8 to 12 2.2% 2.1% 2.2% 2.1% 1.9% 1.1% 1.0%12 to 16 1.8% 1.9% 1.9% 1.7% 1.2% 1.2% 1.2%16 to 20 1.1% 1.5% 1.1% 1.0% 0.9% 0.9% 0.9%20 to 24 0.9% 0.8% 0.9% 0.7% 0.7% 0.7% 0.8%

Combine Segments in AdWords

1. Select segment in the dimensions tab

2. Select segment in the download interface.

How many dimensions should be combined?At some point, your data volume will be too small. The first step away from using average values will have the greatest impact.

• Based on Analytics / AdWords reports

• Proactively create segments by purchasing power

• By branch network

Best Practice for low-data segments:Form regional clusters: Top vs. Rest

Adjust Your Bids by Region

Value per Visitor in Analytics

Purchasing Power in

Germany (GfK)

Further Segmentation (Based on Data Available)

0% 50% 100% 150%

112%

101%

92%

73%

Conversion rates of fashion retail industry

100% = average

Frankfurt

Darmstadt

Wiesbaden

Fulda

80%

90%

100%

110%

120%

109%

106%

102%

96%

Differentiating your bids by region will enable you to generate a sales increase of 20% – while your cost-turnover ratio remains unchanged.

Saxony-AnhaltNRW

Hesse

Bavaria

Maximum: Differentiate by RegionsCoatsSell better in New Hampshire

CR total Shorts Coats

New Hampshire 2.3% 1.4% 2.6%

Georgia 1.8% 1.5% 0.8%

Use different regional bid modifiers forevery product category

ShortsSell better in Georgia

Use Semantic Keyword Characteristics

[BRAND] [DISCOUNT] vs. [BRAND] [BUY] adidas cheaper vs. adidas shoplipsy wholesale vs. buy lipsy

Clustering keyword performance by characteristics such as:• Brand, category• Purchase-signal words• Colour, target groupwill help you place your bids more quickly and accurately.

Example: bargain hunters

Result: Bargain Hunters Are Unprofitable

[BRAND] [DISCOUNT] vs. [BRAND] [BUY]

70%

75%Small shopping cart values

Low margin per purchase

58%Low conversion rates

72%Low rate of new customers

Keywords which still have low click rates, but which fall into the category described above, should be proactively priced down.

CPO ROI CLV

Evaluate your sales results discriminatingly

Accurate evaluation of success

Cost-Turnover

ratio

Which keyword is worth more?

Ray Ban – Aviator EUR 130.49

Ray Ban Sunglasses Daily Lenses 30 Piece

Daily Lenses SetEUR 24.99

Identical in terms of CPO

Ray Ban – AviatorEUR 130.49

Daily Lenses SHEUR 24.99

CPO:EUR 15 Bid: EUR 0.40 CPO: EUR 15 Bid: EUR 0.40

If you set a CPO target value on the account level, all purchases will be valued the same, even if customers’ shopping cart values differ.

Cost-Turnover Ratio Accounts for Revenue Levels

Ray Ban – AviatorEUR 130.49

Daily Lenses SHEUR 24.99

Cost-turnover ratio: 11%Bid: EUR 0.70

Cost-turnover ratio: 60%Bid: EUR 0.10

In terms of cost-turnover ratio, the contact lenses are of less interest to advertisers, and the bid is lowered.

Cost-turnover ratio = CPO / Shopping cart value

Daily Lenses Generate Higher % Profit Margin

Ray Ban – AviatorEUR 130.49Margin: 20%

Daily Lenses SHEUR 24.99Margin: 60%

ROI: 74%Bid: EUR 0.70

ROI: 0%Bid: EUR 0.30

The daily lenses as a private label generate a higher percentage profit margin. The ROI takes short-term profitability into account .

ROI = ( Shopping cart * Margin / CPO ) – 1

Follow-up Purchases of Contact Lenses Boost CLV

Ray Ban – AviatorEUR 130.49

Daily Lenses SHEUR 24.99

CLV: EUR 11 Bid: EUR 0.52 CLV: EUR 30 Bid: EUR 0.60

In contrast to the sunglasses, the contact lenses generate follow-up purchases. These future margins lead to higher bids today.

CLV = Customer Lifetime Value. Long-term profit.

Bid Overview

Ray Ban – AviatorEUR 130.49

Daily Lenses SHEUR 24.99

CPO: EUR 15 Bid: EUR 0.40KUR: 11% Bid: EUR 0.70ROI: 74% Bid: EUR 0.52

CLV: EUR 11 Bid: EUR 0.52

CPO: EUR 15 Bid: EUR 0.40KUR:60% Bid: EUR 0.10ROI: 0% Bid: EUR 0.30

CLV: EUR 30 Bid: EUR 0.60

The CLV model will increase the bids that generate high numbers of valuable new customers – on the condition that you track margins and new customers.

Segmenting keywords leads to improved conversion rates

Test ad texts separately for brands and ad group

Segment Match Types and Ads

AdWords Basics: Segmented Search Queries

Enter the search query of a broad match as a keyword:Differentiated bids, better ads

Broad match performance

TV

TV

LCDTV

LED

TV

2%

1%

0.5%

0% 10,000Clicks per month

4,000 8,000 10,000Clicks per month

Search query performance

ONE average bid

Increase in Average Conversion Rate

More traffic for high-conversion keywordsbecause of:

Good search queries will receive more traffic

0.5%

2%

1%

0%TV

CR

LCDTV

LED

TV

Better ads due to separate keywords

1. Higher bids2. Ad quality3. Quality score

Potential:50% increase in sales due to better ads alone

Testing Ad Texts for Brands

Slogan Adidas Lipsy D&G Aggregate

Sales argument + + - +

Best argument Free shipping 24 hour delivery None Free shipping

Call-to-action + + - +

Best call-to-action Use Code Shop - Shop

„Wide selection“ + + + +

What works best as a slogan in the aggregate may not necessarily work best for individual brands!

Careful when Aggregating Ads!

The same applies when working with ad groups:

Results may be distorted in the aggregate and may not accurately represent individual results.

Total Clicks Impressions CTRFree delivery 54944 7154546 0.8%50% discount 27087 2584300 1.0%

AdGr 1 ClicksImpressions CTR

Free Delivery 13278 180238 7.4%50% discount 3449 315416 1.1%AdGr 2 Clicks

Impressions CTR

Free Delivery 16383 124023 13%50% discount 19358 192810 10%AdGr 3 Clicks

Impressions CTR

Free delivery 25283 6850285 0.4%50% discount 4280 2076074 0.2%

Other Important Segments

• PLA targets: all products brands products

• Remarketing groups, depending on website performance

• Mobile vs. Desktop

Best Practices

1. Segment keywords continuously

2. Optimise ads continuously

3. Bid modifier on campaign level once a month• Weekdays, time of day• Regional• Mobile vs. Desktop

The first step away from using average values will have the greatest impact. Depending on the data available , it may be useful to segment further.