11 best practices for programmatic...

11 BEST PRACTICESFOR PROGRAMMATIC ADVERTISING

PRINCIPAL AUTHORS

ROLAND SIEBELINK, HEAD OF CAMPAIGN QUALITY & PRODUCTIVITY, ROCKET FUEL INC.

JARVIS MAK, SENIOR VICE PRESIDENT, CUSTOMER SUCCESS, ROCKET FUEL INC.

…and the setup tips that marketers need

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11 Best Practices For Programmatic Advertising More questions? Contact us at 020-3651-1300 or [email protected]

This whitepaper is about

the practical ways to make

programmatic advertising more

effective. It focuses on how to

set up programmatic advertising

programmes for success, and how

to coax the best possible

performance out of them.

People who will benefit from

this whitepaper include media

planners, marketers, ad-operations

experts, and media analysts whose

primary focus is to actually run an

advertising programme, as opposed

to buying it.

HOW TO AVOID COMMON PROGRAMMATIC ERRORS

Clearly, marketers have a lot of

questions about programmatic

buying, and a need for

simple answers. The world of

programmatic buying is evolving

so quickly that what might have

been accepted as general

knowledge last month could be

completely obsolete next month.

Rocket Fuel‘s “always-on“

philosophy of programmatic

advertising lets

us test, and optimise advertising

programmes every minute of the

day, every day. As soon as a

programme can be improved, it is.

This "always-on" approach is a

vast improvement to what

marketers have long considered

best practices in traditional

advertising. As in every paradigm

shift, a little extra knowledge can

go a long way toward helping you

gain a sustainable advantage over

your competitors.

BEST PRACTICES FOR PROGRAMMATIC EXECUTION

This whitepaper is a checklist

of simple tactics that can help

you make your programmatic

advertising programmes more

successful. We’ve also included

examples of actual user cases

throughout to help illustrate the

best practices we describe.

PLEASE NOTE:

This whitepaper does not focus

on what programmatic advertising

is, what makes it different from

traditional media buying, or how

to select a good programmatic

buying partner. It assumes that

the buying decision has already

been made. If you are looking for

answers to those pre-buying-

decision questions, we strongly

recommend downloading the

whitepaper, “10 Questions on

Programmatic Buying... and the

Answers Marketers Need.“

INTRODUCTION

mailto:sales%40rocketfuel.com?subject=%2211%20Best%20Practices%22%20whitepaper

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Artificial Intelligence. Real Results.

11 BEST PRACTICES

ONE: INTEGRATE PROSPECTING AND RETARGETING ........................................... 04

TWO: COLLECT DATA ON EVERY PAGE .................................................................... 06

THREE: OPTIMISE TOWARD REAL BUSINESS GOALS ........................................... 08

FOUR: RELAX YOUR CONSTRAINTS ........................................................................ 10

FIVE: TEST DATA MODELS HEAD TO HEAD .............................................................12

SIX: TEST MULTIPLE CREATIVE VARIATIONS LIVE ..................................................14

SEVEN: ENTRUST DAILY OPTIMISATION TO THE ALGORITHMS ............................16

EIGHT: EMBRACE VIEW-THROUGH CONVERSIONS .................................................18

NINE: SHARE RESULTS IN REAL TIME ......................................................................20

TEN: RANK VENDORS OPENLY . ................................................................................22

ELEVEN: SELECT A PROGRAMMATIC PARTNER THAT EMPOWERS ALWAYS-ON MARKETING . ................................................ 24

http://rocketfuel.com/

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ONE:

INTEGRATE PROSPECTING AND RETARGETING Programmatic advertising works best

when it’s allowed to combine upper-

funnel and lower-funnel efforts

in the same programmes. The best

practice is either:

1. Do not delineate funnel stages at all,

and let programmatic vendors compete

fairly on full-funnel effectiveness, or

2. if the advertiser insists on delineating

funnel stages, let each programmatic

vendor choose which stages they want

to compete in.

SHARE VALUABLE MODEL LEARNINGS

Having access to all funnel stages multiplies the amount

of data generated, which greatly speeds up learning

cycles and increases effectiveness.

Assigning certain vendors only to specific parts

of the funnel, such as using separate vendors for

prospecting and retargeting, means each vendor

needs to build up its own data about consumers,

interests, actions, and behaviour.

The best practice here is to let vendors work on this

funnel end to end. This enables them to leverage

more data and capture more consumer actions in their

algorithms, thus deriving far better funnel models for

the advertiser‘s product.


SPLIT THE RETARGETING POOL

It used to be a best practice to prevent bidding wars

for retargeting impressions by assigning retargeting

exclusively to one vendor and prospecting to others.

This is no longer the case.

First, splitting the retargeting pool between different

vendors prevents bidding wars more efficiently than

exclusivity does, with far more day-to-day control.

Second, letting programmatic vendors compete full-

funnel provides more insights and a better use of the

most advanced technology. Ultimately, this provides a

better ROI than letting “specialised“ vendors cherry-pick

the easiest conversions without replenishing the funnel.

Finally, retargeting can be so expensive that it is crucial

to keep comparing the ROI—not just between this month

and last month, but also between competing vendors.

USE THE SMARTITIONER SCRIPT

Setting up a simple script on the advertiser‘s website

will help split the retargeting pool fairly across several

programmatic advertising partners.

1. Download the Smartitioner script, which

Rocket Fuel has contributed to the open-source

community.

http://www.github.com/rocketfuel/smartitioner

2. Pick the vendors that you want to split the

retargeting pool between and assign a percentage

of the allocation to each of them. For example,

you can give one partner (the incumbent) 75% of

the retargeting traffic, and another partner (the

challenger) 25%.

3. Implement the script on the advertiser‘s website,

or use a tag-management system that cleanly

splits the retargeting pool. The more flexibility

you have to adjust the allocation, the better.

4. Remove all other vendor pixels from the

advertiser’s website.

5. Your retargeting pool will now split cleanly

between the vendors defined, according to the

allocation you determined.

6. After an initial evaluation period, begin adjusting

your retargeting allocation in favour of the

better-performing partner. You‘ll want to confirm

sustained performance before switching over

completely to a single partner.

7. Don‘t rest on your laurels. Implement another A/B

test six months to one year after you begin so

you can ensure your partner of choice continues

to be the strongest competitor.

FOR EXAMPLE: DOUBLED PERFORMANCE FOR A CREDIT-CARD CLIENT

A major credit-card company wanted us to split their

campaigns between prospecting and retargeting goals,

with 50% of the budget devoted to each, and using a

separate creative for each stage.

When initial CPA results were disappointing, the

agency recommended running one end-to-end tactic

including both prospecting and retargeting. This let our

algorithms decide how to balance the stages, and which

creative to serve, at which moment.

Almost instantly, we saw the prospecting/retargeting

balance move away from 50% /50% to 85%/15%, and

the CPA for the overall programme drop by more than

half. Once clients try integrated prospecting/

retargeting tactics, they rarely return to separate

tactics again.

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TWO:

COLLECT DATA ON EVERY PAGE/URL

Programmatic advertising works

best when it knows as much

as possible about consumers

previously exposed to the

advertiser‘s owned or paid

media. This is why advanced

programmatic vendors ask an

advertiser to not just place a pixel

on a conversion page (or a few key

pages on their website), but on all

possible pages and other digital

media that users may access.


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LEARNING FROM NON-CONVERSION ACTIVITY

Marketers often believe that pixels only matter for

retargeting. The truth is that information about the

consumer is valuable at every stage of the funnel.

The earlier that programmatic advertising vendors can

build a profile of an anonymous consumer, the more data

they can gather about the conversion funnel, and the

easier it is to optimise the entire advertising programme

toward the funnels that have proven most ideal.

DON‘T LIMIT EXPOSURE OF A VENDOR PIXEL

The most common error is to limit pixels to the

conversion page. The few seconds of effort webmasters

save by not placing a universal pixel could well result in

an ROI that is hundreds of thousands of pounds lower

than it could have been.

The next most common error is to place the pixels of

competing vendors inconsistently. Fair competition

requires a fair exchange of consumer data, which can

only be achieved if each competitor has the same

number of pixels in the same places.

The third most common error is reusing the same pixel

for vastly different marketing activities, without passing

a parameter where the pixel was placed. This can be

confusing to the programmatic partners‘ algorithms.

PLACE A UNIVERSAL PIXEL AND A CONVERSION PIXEL

A good programmatic advertising vendor will propose

at least two pixels: One specific conversion pixel for the

conversion page and one universal landing pixel for all

other pages.

It is a best practice to implement those pixels as per the

recommendations of the vendor:

• The universal landing pixel in the footer that gets

attached to each page

• The conversion pixel on the conversion page

In addition, another best practice is to have separate

pixels for all the different marketing channels.

FOR EXAMPLE: QUADRUPLED PERFORMANCE OVER DIRECT COMPETITOR

Placing a pixel on every page can drive up performance

2–4x, a much bigger factor than many marketers might

guess.

We can illustrate this with an interesting case of two

telecom advertisers—let‘s call them ComTel and TelCom.

ComTel and TelCom offer similar products and services

at similar prices. They focus on similar segments, and

run similar advertising programmes. The only difference

is ComTel had a pixel on its conversion page only,

whereas TelCom had a universal pixel that gathered

data on every page.

The gap in their performance was striking. ComTel‘s CPA

was invariably less than half of TelCom‘s, and—more

typically—closer to a quarter.


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Programmatic advertising drives the best results for advertisers when

agencies and marketers are able to move beyond the short-term

advertising goal. If they can identify the underlying business goal, and

link that goal directly to the programmatic efforts, marketing results will

suddenly become much more relevant for the advertiser, making the

contribution to the advertiser‘s bottom line rise exponentially.

THREE:

OPTIMISE TOWARD REAL BUSINESS GOALS


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ROI IS HIGHER WHEN DRIVING BIGGER-PICTURE RESULTS

An example is moving from a CPA focus to a customer

lifetime value (CLV) focus. Suddenly, the programme

will ignore the same old repeat customers and drive

new consumers to the advertiser—people who are

highly likely to buy multiple times and at a high value.

The perceived ROI of the advertising programme can go

up by several factors, and will rise higher, the closer it is

tied to the advertiser’s strategy and bottom line.

For example, an advertiser growing its business in

new markets, given the difference in awareness levels

alone, will have little chance of success if it expects

the same CPA it enjoys in an existing market. But focus

the same programme on the discounted cash flows of

future customers, and the new markets suddenly look

far more attractive.

DON‘T REDUCE BUSINESS GOALS TO LOWEST COMMON DENOMINATORS

Being fully aware of the business goal for the client,

but “translating“ that into a pure marketing goal for the

programmatic advertising vendors is a common error.

This is partially based on habit, and partially on

insecurity about programmatic advertising vendors not

being able to measure something outside of the core

advertising metric toolbox.

DO SHARE THE REAL BUSINESS RESULT AND UPDATE IT REGULARLY

A best practice is to share the real business result, or

even to ask for it if the advertiser did not include it

in the original briefing. Allowing the most advanced

programmatic advertising companies to optimise

directly toward this business metric will generate

enormous success. It will also show a much clearer

differentiation between the kinds of optimisations

that different programmatic advertising platforms are

capable of.

FOR EXAMPLE: MAXIMISED CASH INFLOWS FOR NEW CHECKING ACCOUNTS

After the financial crisis hit, banks were scrambling for

consumer pounds and advertising their savings

accounts aggressively. A leading online bank found that

its programmes persuaded many consumers to open

bank accounts, but that those consumers did not

necessarily fund those accounts with much cash. We

worked with the agency to shift the focus from

accounts opened to aggregate pounds flowing in.

This optimised programme generated as much as a 20%

lift in bank accounts that are profitable for the bank,

thus helping the bank to drive much higher ROAS.


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Programmatic buying works best

when it can make full use of all

the consumer data available, then

amplify successful conversions to

new audiences that exhibit many

of the same data points.

FOUR:

RELAX YOUR CONSTRAINTS

The best DR marketers allow the programmatic

models to discover these new data points and

generate conversions even in unexpected corners of

the market, rather than constraining advertising to

traditional segments.

IMPROVES LEARNING AND REDUCES WASTE

Traditional marketing tends to avoid waste by limiting

spending to closely prescribed target segments, then

selecting media that claim an acceptable degree of

reach into that segment.

Advertising programmes, however, buy every single

impression individually and have millions of data points

to predict whether an impression will ultimately lead to

a conversion. They minimise waste by the very act of

optimising toward the programme goal, and no longer

need the traditional trinity of segments, content, and

reach.


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BEST PRACTICE FOR BRAND MARKETERSTrying to discover new segments does not fit with brand programmes.

Brand marketers have audience

composition and reach as core

performance measurements, so the

approach must be different for those programmes.

The good news is that programmatic advertising programmes are excellent

at driving a high reach within a very

specific audience composition. The key to success is to optimise the programme

for that measure and not for an

inaccurate proxy measure such as clicks.

Advanced programmatic advertising

companies have permanent

partnerships with brand-measurement

companies like Nielsen and comScore to

integrate the programmatic advertising programme with tried-and-true brand

metrics, and even to optimise toward

these brand metrics in-flight.

DON‘T FORCE A TRADITIONAL WAY OF SEGMENTATIONLimiting programmatic DR programmes to only

impressions within a certain segment or on certain

publications will often be counterproductive because

this will limit both:

•Conversions that happen to fall just outside of

the segment

•Learnings for more advanced modeling of the

consumers most likely to respond to the

programme

We have seen many examples of programmatic

programmes with “hard constraints“ on segments or site

lists under-performing because the algorithms could

simply not learn enough about this limited set of

consumers to discover the programme‘s additional

market potential.

DO SPECIFY DESIRED SEGMENTS AS STARTING POINTS

The most effective way to use audience segments in a

programmatic DR programme is to specify them as

“soft constraints“:

1. Set a clear goal and a numerical constraint for the

programme performance

2. Limit hard constraints to geographical

constraints only

3. Specify all demographic, psychographic, and other

targeting criteria as soft constraints

4. Let the campaign perform and optimise within the

constraints and build on the starting points given

FOR EXAMPLE: HALVED ACQUISITION COST FOR A POWER COMPANY

Relaxing audience characteristics can double or triple

the impact of an advertising programme.

A major automotive marketer translated its intent to

reach more Spanish-speakers into “only advertise on

Spanish-language websites.“ The resulting acquisition

costs were typically 2-3x higher than the goal

originally intended.

A major power company started out with a troubled

advertising programme too, defining micro budgets for

each DMA. Once we removed this restriction and

focused on the same geography at a state level, the CPA

dropped by more than half.


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On the other hand, buying third-party data models and

investing in the quality of first-party data segments is

expensive. A simplistic programmatic buying

programme may shift a large chunk of the efficiencies

gained in media buying toward data buying, unless it

tests aggressively which data actually works.

The best approach for marketers is to handle data the same

way they test vendors: Try out as much as possible, but

never commit large budgets until performance is proven.

DON‘T FOCUS ON SPECIFIC DATA MODELS DIRECTLY

Simplistic programmatic advertising programmes buy

multiple third-party data models, maximise reach and

frequency among the consumers in these segments,

and then try to find more consumers that “look” like the

consumers that ultimately converted in these segments.

But because nobody can reliably predict the validity of

data, this approach is generally inefficient. It takes the

validity of the third-party data models for granted, and

pays for their use no matter what their influence on the

marketing results is.

DO INVEST IN DATA THAT IS PROVING ITS WORTH

The best practice is to suggest all of the possible data

sources to the programmatic advertising vendor, but to

consider them just a starting point.

Advanced programmatic advertising algorithms will run

massive tests of many combinations of data sources,

Marketers gaining experience with programmatic buying start to

notice how their advertising becomes less dependent on the sites

and apps where ads are served, and more on the right consumer data

underpinning the selection of impressions. This is why it makes sense

to add more data.

FIVE:

TEST DATA MODELS HEAD TO HEAD


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messages, and context, and will quickly figure out which

combinations of data points are most successful and

rise to the top.

Many other data sources will remain below the surface

and not show significant lift for a given programme

objective even though they may have performed well for

a different programme or client, or may do so in the

future.

FOR EXAMPLE: MODELED AUDIENCES SEEDED WITH DATA MODELS OUTPERFORMED BY 2.5X

A major CPG advertiser noticed that the third-party

data models that they had based their programme

on showed large differences in brand lift. At the

recommendation of the agency, it decided to test all

data models against an algorithmic-synthesised model

of their intended audience.

While two out of eight third-party data models

performed better than the synthesised model, six

out of eight did not, dragging overall brand lift

down 45%. Naturally, the client decided to move the

budget into the performing data models and the

synthesised model.

A major automotive manufacturer saw an equally

impactful difference in a head-to-head test for

behavioural targeting: the dynamic model did almost

2.5x better than the data models, with a 59% lower

CPA.


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While programmatic ads need to

look like a small print ad to be

effective, the big difference with

digital is that there is no need

for “final“ creative. If the goal is

to learn and optimise as much as

possible during the programme,

then it is actually

counterproductive to have “final“

creative at any point.

SIX:

TEST MULTIPLE CREATIVE VARIATIONS LIVE

MAXIMISE LEARNING AND EFFECTIVENESS

Programmatic advertising is most effective when it

can test and revise (or “learn“) across many cycles. This

learning should not be limited to tactics and settings;

it should also include the messaging. The reality of

programmatic advertising is that very subtle differences

in ads can result in strikingly different response rates.

Let the data from the response rates be your guide.

DON‘T TRY TO PICK THE SINGLE BEST CREATIVE UPFRONT

One of the worst errors in programmatic advertising

occurs when advertisers try to develop a single

“perfect“ ad rather than keeping a few variations on the

table. Programmatic advertising programmes do better

when they start with a few flavours of an ad and then

allow the market to decide which one(s) works best with

which consumers and in which context.

DO TEST VARIATIONS AND ADD POLISH LATER

The goal during the first week (or maybe even the first

day) is simply to learn as much as you can about which

creative elements work best. The algorithms will do

massive testing that yields a massive amount of data

about the best message, the best image, the best

promotion, and the best call to action.

FOR EXAMPLE: INCREASED PERFORMANCE AND LEARNING

A well-known financial services niche publication

started running just one creative. While the client was

happy with the initial performance, tests with additional

creatives kept increasing results. As a result, more

creative variations were added.

The client is now at a total of 47 creative variations,

across all creative types, sizes, and funnel stages.

Average performance is now 82% better than when the

programme first started.


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Many marketers, especially when working directly for the advertiser

rather than at an agency, are very hands-on when it comes to

managing their budgets. They are used to making constant changes

to the budgets based on the performance of the most recent

few days. While we applaud this hands-on management in

traditional digital media or in search advertising, it can be

counterproductive in programmatic buying, especially in a

fully algorithmic environment.

SEVEN:

ENTRUST DAILY OPTIMISATION TO THE ALGORITHMS


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MANUAL TWEAKING HURTS PERFORMANCE

The programmatic system already takes the variability

of the environment into account and adapts to it

constantly. Changing the goals resets the learnings and

can make previous learnings less valid.

DON‘T OVERIMPOSE OR OVERCORRECT

• The first common error is to correct manually and

reset the learnings before the algorithms have had

a chance to correct themselves.

• The second common error is to correct for naturally

occurring variability of the kind that an algorithm

can recognise and manage, but stressed-out human

marketers might overreact to.

• The third common error is to overcorrect. Marketers

may set a lower CPA than they can really afford,

just to “have the result reach the middle.“ In such a

constrained system, the outcome may be that the

partner‘s algorithm is only able to deliver a fraction

of the volume at the more aggressive goal.

DO LEARN FROM THE MASSIVE TEST RESULTS

Instead, a best practice is to set a clearly measurable

programme objective and let the algorithms do their job.

• Be honest about the real programme objective and

avoid “padding“ that number for better performance.

• Let the algorithms run, and provide the vendors

with honest feedback about performance (see

“Rank Vendors Openly“ on p. 22).

• Avoid making manual changes to content, segments,

objectives, and budgets until the algorithms have

run at least a week with stable settings.

• Delve into the insights that the algorithms’ massive

tests provide, and adapt other parts of your

programme to the new learnings gained.

FOR EXAMPLE: 45% IMPROVED PERFORMANCE AT 68% HIGHER BUDGET

We worked directly with the marketing team of a well-

known women‘s-apparel retailer. The marketing team

was extremely hands-on, prescribing exact daily and

weekly budgets and swapping out creative every single

day. This threw off the automatic calibration of the

models so much that the client missed its KPIs by as

much as 50%.

A major eyewear e-tailer had a marketing team that

was very hands-on, resetting budgets on a daily basis.

Looking for better performance at a higher scale, it

allowed our algorithms more freedom to move budget

between channels and between days of the month.

This flexibility made such a difference that CPA dropped

45%, even with a 68% budget increase.


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Consumers typically see ads numerous times: during a Google search, on

Facebook, as a display ad, in an email, or on an affiliate site—sometimes

all of the above. Therefore, it makes little sense to give full credit to

the last time a person clicked on the ad before converting. Effective

advertising programmes draw in customers every step of the way.

EIGHT:

EMBRACE VIEW-THROUGH CONVERSIONS


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STRONGER FUNNEL GROWTH

Apportioning credit to multiple touch points before a

person converts is not that difficult, and it pays huge

dividends. Embracing the effectiveness of view-through

conversions is a key step to capturing the full benefits

of programmatic advertising.

Experienced marketers understand the importance of

“top-of-the-funnel“ efforts designed to plant a seed in a

customer‘s mind. For most consumer products, only 14%

of consumers are said to be open to alternatives at the

actual purchase stage. This means that at least 86% of

the purchase decision is made before the last click.

DON‘T OVERSIMPLIFY YOUR ATTRIBUTION

Multiple analyses also show that people who click on ads

represent a tiny, and generally unattractive, demographic

segment of Internet users. One programme seeking

18-24 year-old city students of wealthier backgrounds,

for example, found that a majority of clickers were

retirees in poor households and rural environments.

Marketers that insist on click attribution will ultimately

find their marketing returns collapse. This is simply

because they are focusing on the skewed audience that

clicked on an ad in order to convert.

DO CHAMPION STATE-OF-THE-ART ATTRIBUTION

We recommend implementing a robust multi-touch

attribution framework that credits every stage in the

funnel appropriately, and updates programmes with

data in-flight (see “Share Results in Real Time“ on p.

20).You can build a robust attribution framework by

experimenting iteratively with the mix of partners,

channels, and attribution allocations across a few

programmes. Most likely, you can reach the same

bottom-line results much more efficiently with fewer

partners and fewer touch points.

FOR EXAMPLE: 99% OF ORDERS RESULTED FROM VIEW-THROUGHWe work with one of the biggest fast-food delivery chains,

driving both in-store sales and increasing the effectiveness

of TV advertising with programmatic support.

Initially, both the advertiser and the agency were

convinced that they should give credit only for

purchases attributable to a click. However, Nielsen

research proved clearly that there is “virtually no

relationship between clicks and brand metrics or offline

sales.“ ComScore supported this finding, saying that

only 16% of consumers ever click on ads, and that 8% of

users account for 85% of all clicks.

In a programme we ran for a major restaurant business,

clickers were also very different from converters.

Converters tended to be 18–44 years old, whereas

clickers skewed toward 65+/retired. Converters tended

to be interested in movies and video games, whereas

clickers preferred golf and ladies’ leisure.

Further research with the agency showed that repeat

customers (those with high lifetime value) were 8.8x

more likely to be view-through converters than click-

through converters. After we showed that click-based

revenue represented less than 1% of total revenue

generated, the advertiser quickly embraced view-

through conversions.


20


Some of the low-hanging

fruit in programmatic

advertising is to share

performance data

with vendors on a

programmatic basis. With

just one login to your ad

server or analytics system,

you can create massive

performance improvement

solely on the basis of how much

the programmatic system can learn

from granular results.

NINE:

SHARE RESULTS IN REAL TIME


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SPEEDING UP THE LEARNING CYCLEProgrammatic buying is designed to respond to changes

in supply and demand in microseconds. To do this well,

it needs up-to-date feedback on how well it is doing for

the advertiser. Direct programmatic access ensures that

the programmatic advertising algorithms can respond to

these fluctuations instantly.

SHARING A PDF ONCE A MONTH IS AN OPPORTUNITY LOST

This means that it is not sufficient to tell your

programmatic buying provider about your results on

a weekly or monthly basis. You also shouldn‘t do it

in a format that is hard to import. And sticking with

manual processes causes frequent errors and delays in

importing the performance data back into the system,

which results in inconsistent calibration and reporting.

data from your systemBy giving a programmatic vendor real-time access to

the same data that you use to track their advertising

results, the vendor can optimise their programme in

real time rather than weekly or monthly.

The most common performance tracking

systems are the third-party ad servers. But,

if your “source of truth“ for marketing performance is

a web-analytics system like Omniture, then it‘s critical

to provide that feedback to your partners as often as

possible. If the web-analytics data conflicts with the

third-party data, but it‘s the web-analytics numbers that

matter to senior executives, then that‘s what all partners

need to be using. Otherwise, their systems are optimising

off the wrong data.

FOR EXAMPLE: 2X PERFORMANCE OVERNIGHT

We should mention that the first benefit of real-time

data sharing is less work for the agency or marketing

team. Once clients move to real-time data integration

with their ad server or analytics system, they notice

that campaigns start to auto-optimise without any

manual intervention. This productivity gain alone is a

massive benefit for busy marketers.

This optimisation, of course, also provides a

performance boost. After a premium automotive brand

decided to provide us with a login to its ad server, the

automatic optimisations kicked in and performance

doubled overnight.

Allow your vendor to pull


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A second aspect of sharing

performance is easy to accomplish

and highly effective too: Simply tell

each partner how they perform

against their competitors.

TEN:

RANK VENDORS OPENLY


23


ENABLES CALIBRATION OF PERFORMANCE METRICS

The very nature of programmatic advertising is that it

has advertising programmes running on automatic pilot.

The software to run these programmes works best

when it can regularly calibrate itself to the performance

that the client sees.

DON‘T CANCEL A VENDOR IMMEDIATELY

This is why it is better to share relative performance

openly before taking a vendor off the plan. Whereas

performance with traditional media vendors is typically

fixed for any given programme, programmatic buyers

have at least a few levers they can pull to push

performance.

Cancel them too early, and you may miss out on a part of

the programme that could have performed better.

Smart programmatic vendors strive to be the optimal long-

term performer for the advertiser. Their goal is to drive

performance at a level that is better than competitors’,

but to also be scalable to a high volume at any given point

during the programme and over time. Calibration can help

facilitate a switch to a shorter-term perspective, when that

is what the advertiser really wants.

DO TELL EACH VENDOR THEIR RANK WEEKLY

We recommend sharing relative performance with all

partners on (at least) a weekly basis.

1. Rank all partners on the plan by the one metric

most important to the advertiser.

2. Tell each partner what place they reached in the

ranking, and indicate if the gaps between them

and their rivals are large or small.

3. Ask the best-performing vendors how much

more budget they could take at similar levels of

performance. The best programmatic vendors can

predict this with a high degree of accuracy.

FOR EXAMPLE: ALWAYS SHARE INFORMATION TO HELP ENSURE HIGHEST ROI

In one particular case, our algorithms were beating the

internal client goal, but the client did not inform us and

we could not see the same performance in our numbers.

We therefore recommended that they cancel with us

in order to work with another partner (not knowing we

were the best performer on the plan). If our system

had been re-calibrated on the basis of the performance

that the client saw, we could have scaled the campaign

significantly, delivering a much higher return on

advertising spending than the client ultimately

obtained. It was an opportunity lost for both of us.

On the flipside, a leading online music-distribution

service initially declined to provide relative performance

feedback. Since our programme beat the official CPA

target, the team did not see the need to tweak

performance versus scale and sustainability.

After the client informed us that performance was more

important than volume and that another vendor was

driving better CPA results, albeit at a lower scale, some

tweaks quickly drove a 15-20% performance improvement.

More importantly, this discussion also generated more

insight into the client‘s real business goal: driving better

prospects with a higher potential lifetime value. After we

learned that, we quickly optimised the programme, to much

higher satisfaction of the client.


24


ELEVEN:

SELECT A PROGRAMMATIC PARTNER THAT EMPOWERS ALWAYS-ON MARKETING


25


We hope that this whitepaper has shown many actionable ways to make

your programmatic advertising run better.

While some of these tips can be applied liberally in

a self-service setting, the reality is that the vast

majority of programmatic advertising runs through a

full-service relationship with one or more specialised

vendors. Therefore, our final recommendation is to

be critical about vendors and to pick the ones that

ultimately deliver the best ROAS (return on ad spend)

to the advertiser.

Obviously, advertisers may want to take into account

buying criteria like transparency, data access, low

margin, and a beautiful user interface. But, in the end,

we find that the best practice is to focus on attaining a

sustainable ROAS first and foremost. If you do that, the

rest will then fall into place.

TWO VENDOR “MUST-HAVES”:

1. SPECIALISTS WITH PROVEN TRACK RECORDS

Choosing the right partner is important because

programmatic advertising is changing much faster,

and thus is much less user-friendly to operate

than, say, search advertising.

2. DON‘T HAVE MULTIPLE VENDORS ON THE PLAN

“FIGHT IT OUT“

Choose a number of partners for your plan, and

give each every opportunity to show you their

best stuff—letting them know how they are doing

against (anonymised) competitors.

Since programmatic depends so much on learning and

strategic data integration, the worst way to choose

programmatic advertising partners is to have a half

dozen or more seemingly comparable partners “duke it

out“ without utilising some recommended best

practices. Instead, choose one or two partners that

have long and proven track records, and the expertise,

the technology, and the roadmap to build a long-term

strategic relationship with your company.

Think of the vendor-selection process almost as a

technology decision—one that is more far-ranging than

running a media plan for one month. With that in mind,

it’s clear that it should take plenty of time to investigate

various vendors for the best long-term fit. The best

programmatic marketers think about adapting their

strategies for an always-on marketing world. Rather

than thinking about campaigns with fixed starts and

ends, they think about marketing as a 24/7 practice, and

advertising that learns and improves doesn’t need to

stop or sleep to improve ROAS.

That said, you should also run a head-to-head test at

scale to ensure that each partner produces outstanding

results time and time again.


26



27


The best way to run traditional

advertising is often not the

best way to run programmatic

advertising. This whitepaper has

outlined eleven best practices

to get the most out of your

programmatic marketing efforts,

and we hope you will be able

to apply most if not all of these

practices across all of your

programmatic advertising

programmes.

Choosing the right partner is

crucial. As the most successful

programmatic advertising platform,

Rocket Fuel is laser-focused on

delivering optimal advertising

results, day after day. Our

“always-on marketing“ approach

to programmatic means your

programme results are tested,

reviewed, and optimised all day

and all night. With this strategy,

we can take your advertising

results and marketing ROAS to

new heights.

CONCLUSION


ADVERTISING THAT LEARNS®

Questions? Call us on +44(0) 203 6511 300 or

email [email protected]

11 best practices for programmatic...

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