OPENING THE BLACK BOX

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March 2014

OPENING THE BLACK BOX

Programmatic campaign transparency

comes to light

Principal Authors:

Shachar Radin Shomrat

Chief Marketing Officer

Harel Amir

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Introduction

From black box to glass box

Media transparency

Audience transparency

Mobile transparency

Channel transparency

About myThings

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“

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I’ve been running retargeting for a

few years now but I have learned

practically nothing from it.

CMO of a large fashion retailer

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Introduction

Programmatic advertising has disrupted the industry – that much is clear. The ability to leverage big data to buy media has revolutionized campaign efficiencies and dramatically increased ROI.

However, despite the growing importance and recognition that data is the fuel that pushes digital marketing forward, there’s no real visibility into the data, which is often limited to basic campaign-level performance metrics such as impressions, clicks and CTR.

For more and more advertisers, particularly the tier ones with access to significant first party data, strong performance is almost a given. They are demanding added value. The days characterized by ‘I don’t know what’s working but I don’t really care as long as it does’ are becoming a thing of the past. As one executive with whom we’ve recently met phrased it:

In recent months, we’ve been hearing this theme time and time again. Marketers are looking for guidance and tools to navigate what has become a complex space. They want to understand the inner workings of their data-driven campaigns – what’s working and what’s not, which patterns emerge and what can be learnt from the behavior of their audience that can be applied not only in their retargeting campaign but also across all their marketing activities.

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From black box to glass box

With growing demand from savvy advertisers to know the ins and outs of their campaigns, the following are ways in which this new standard of visibility can come into light:

Media transparency - performance per domain

Media transparency enables advertisers to gain access to performance data per media outlet, providing insights about how the same campaign performs on different sites. Running a brand’s ads through ad exchanges and ad networks means a campaign can stretch out to hundreds or even thousands of sites. Knowing exactly where a campaign is running – both on a domain and sub-domain level (rather than on an exchange or network-level) – and how each is performing can prove highly beneficial to a brand as it pinpoints audience reaction within the context an ad was displayed in. Ultimately, it helps marketers optimize their media buy across all channels and identify key contributors of traffic.

Another important component in media transparency is cost. Disclosing a

retargeting vendor’s margins is directly correlated with the type of business model used in a campaign.

In the case of Cost Plus, the advertiser pays for the media plus a pre-determined mark-up for the vendor. It is therefore a transparent pricing model.

In Cost Per Acquisition (CPA) or Cost Per Click (CPC) campaigns, a cost element is usually not included, as the vendor takes full risk in media buying, requiring greater flexibility to ensure sustainable profit in the long run. This has been the approach since the early days of performance advertising, which began with affiliate marketing and later evolved into personalized retargeting.

In this context, it is important to remember that in the world of performance advertising, return on investment is the #1 KPI. So long as the ROI target is met, media cost is either marginal or irrelevant for many advertisers.

Ultimately, it boils down to preference. If transparency is vital for an advertiser, he should run a retargeting campaign on a Cost Plus model to generate both scale and strong performance. If bottom line ROI is where his focus lies, a CPA or CPC campaign may be more suitable.

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Enhanced audience segment transparency

Audience transparency informs marketers about how each of their audience segments performs within the framework of the same campaign.

Traditional retargeting engines segment users to cold, warm or hot according to their stage in the website funnel – providing the basis for real-time decision-making.

However, for many savvy advertisers, such widely defined segmentation based on one or two dimensions no longer provides sufficient visibility into their audience. If given the option to customize segments based on their specific business goals, they would benefit from far deeper audience transparency.

Business goal

Acquisition

Drive repeat purchases of new customers Lifetime value / Loyalty Cross-selling Reactivation

Relevant parameters used to segment

(including 1st party data) New/existing user Last order date (=false) Registered/non-registered New/existing

Order completed > Lifetime value > Expected order value > Last order value > Loyalty club member (Y/N)

Customers who bought a certain category Last order date

Segment name

Prospects 1st time customers Potential high value customers Electrical customers Fashion customers Dormant customers

Messaging

Get 10% off your first purchase

Free delivery on your next purchase

Join our loyalty club, get $20 to shop at BRAND “Special 3-year warranty offer” “Up to 50% off all home & garden products” New arrivals are here!

Pricing (key factor in bidding decisions) High * Low * High * Medium * High *

What is business-driven segmentation and how does it work? The following table is an example of a business-driven segmentation plan:

* Exact rates determined by advertiser based on the value of each segment

By gaining access to performance data of a detailed segmentation plan like the one outlined above, marketers would be able to gain in-depth visibility - through dedicated reporting and analytics dashboard - into how their most valuable target groups interact with their brand: which segments scale in the assigned pricing, which creative and messages generate the highest engagement and / or profitability, and equally important, which do not – and adjust accordingly.

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Mobile transparency:

OS, device and mobile environment-related data

Mobile transparency allows marketers to understand - through data they can access - how their mobile campaigns are performing in isolation from any other channel, while adding mobile-relevant KPIs: iOS vs. Android, mobile web vs. in-app, tablets vs. smartphones etc. As much as the mobile opportunity is huge, so too is the gap in how little marketers and the industry at large actually know about it. With mobile retargeting in its early days, insights into mobile performance, reach and most behavior are in high demand. Understanding mCommerce patterns and their relationship with advertising is vital to inform decision-making in this new territory.

For example, a recent study we conducted on mobile retargeting found significant differences between mobile and desktop consumers, in addition to tablet and smartphone consumers. The study’s key findings include:

Mobile retargeting drove an additional 18% of retargeting-generated sales, a 46% higher click through rate and a 37% lower eCPC compared to the same desktop campaigns.

The mobile consumer acts fast during the final decision-making phase. The time from the last visit to conversion was 13 (!) times faster on mobile compared to desktop.

+46%

higher CTR _{lower eCPC}

-37%

+18%

Sales when adding mobile to retargeting mix

Compared to desktop retargeting of the same campaigns

Desktop

Mobile

13X faster

3 Significant revenue generator

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Unlike desktop, shopping on mobile remains strong over the weekend (only 6% fewer conversions than weekdays, compared to the desktop’s minus 30%). Similarly, while evening shopping reigns supreme compared to daytime shopping, on mobile the trend was much stronger than desktop with an increase rate double that of desktop (on tablets, the rate jumped nearly six-fold).

Breakdown of mobile conversions had smartphones slightly ahead with 55% vs. 45%; in post click conversions, the ratio was 53% vs. 47%. Ultimately, smartphones drive sales because of greater reach (9x more devices according to June 2013 data from Gartner) while enhanced usability and greater ease to finalize transactions is the main reason behind the tablet’s success.

+31% +33% +46% +80% +24% +26% +10% +14%

Mobile Tablet Smartphone Desktop

Ev en in g (6 -1 1 p .m .) v s. da yt im e Visits Conv. -7% -6% -2% +3% -10% -10% -26% -30% Visits Conv. W ee ke nd s (S at-Su n) v s. w ee kd ay s

Total mobile

conversions

44%

Tablet

55%

Smartphone

Mobile

Post click

conversions

47%

Tablet

53%

Smartphone

Leisure mode

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40.75% 44.46%

11.55% 16.54% 17.16%

10.96% 55.35%

Desktop & Tablet (avg.)

Visit breakdown by deepest stage in funnel

Smartphone

3.24%

Category

Home Product Add to Cart Category

Home Product Add to Cart

Desktop 2.89% 41.48% 44.35% 11.28%

Smartphone 17.16% 16.54% 55.35% 10.96%

Tablet 3.58% 40.02% 44.57% 11.82%

Home Category Product Add to Cart

Tablet and desktop consumers generate similar patterns related to how deep they browse the site’s funnel. The smartphone, however, is significantly different:

o Most smartphone users, 55% vs. ~40% on desktop and tablet, reach product page (showrooming could be a possible explanation)

o 18% of smartphone consumers did not go beyond the home page (compared to ~3% on desktop and tablet)

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Channel transparency (multi-attribution)

Multi-attribution is all about providing advertisers with a view from above so they can understand the role each channel plays in the path towards conversion. In other words: giving credit where credit is due.

In today’s complex digital environment, this form of visibility from above is a must as each channel interacts with the other and plays a different part – whether introducer, contributor or closer.

For example, consider a user who wants to buy a 3D television. What does his path to conversion look like?

3D

Sees display ad

Google

Searches for 3D TVs Clicks an affiliate banner of tv brand Retargeted with display ads and clicks

Google

Searches for coupons

Clicks on PPC ad, goes to site

Completes purchase

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How can credit be allocated?

Let’s explore the allocation of credit across several common attribution models:

1. Last click – PPC ad gets 100% credit

2. Last non-direct click (branded Google

search not credited): Retargeting gets 100% credit

3. First click – Affiliate gets 100% credit

4. First touchpoint: Display ad gets 100% credit

5. U-shaped: Display and PPC get 40% credit each, while affiliate and retargeting get 10% each

6. Linear: All touchpoints get equal credit

7. Time decay:

The older the touchpoint the lower the credit

3D

10% 40% 20% 10% 30% 10% 40% 40% PPC PPC

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A key challenge for marketers today is to figure out their marketing

mix in a way that will accurately reflect the value each link in the chain brings. Regardless of the weight allocated to each channel, one thing is clear: single

touchpoint credit is flawed. Although most marketers understand this, the last-click model is nonetheless the prevalent approach. There are several reasons for this but the primary factor is that switching to complex multi-attribution modeling forces advertisers to make major adjustments in their platforms or even develop new ones altogether. Such action requires time, skills and resources they often do not have. However, the good news is that more and more marketers are moving from last click to last non-direct click. The sophisticated ones apply multi-attribution modeling for the purpose of measurement, often selecting linear (same weight for all in path). A smaller group also uses it for billing.

The most savvy advertisers - a very select circle - go as far as combining several models, especially time decay (the closer to conversion the more credit given) and (funnel) position-based parameters to give more weight to introducers and closers. On top of that, the successful channels are given coefficients to increase their weight even further.

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Regardless of the weight allocated

to each channel, one thing is clear:

single touchpoint credit is flawed.

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Conclusion

Programmatic advertising is changing the way marketers view advertising, whether online or offline. It is generating disruptive changes in the ecosystem. However, its key ingredient – data – is often kept inside a black box even though it holds the key to what marketers actually want more than anything – to find out which exactly work and which do not. The glass box approach – with all its ingredients mentioned in this paper – has a key role in helping digital marketers reach this milestone.

About myThings

Founded in 2005, myThings is the global leader in customized programmatic ad solutions. Running personalized retargeting campaigns on desktop, mobile and Facebook, the company personalizes over 5 billion impressions a month for top advertisers in 30 markets including Adidas, Walmart, ToysRUs, Littlewoods, Very.co.uk, Zalando, Orange, Best Buy, and Microsoft.

myThings’ offering is answering two pains of marketers who run real time programmatic ad campaigns: lack of transparency and template-based automation. It empowers advertisers by providing them with full visibility into the performance patterns of their audience, while creating fully customized programmatic campaigns capable of meeting their specific business goals.

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myThings is redefining programmatic campaign transparency with CLARITY

In the past two years, myThings has been gathering feedback from its customers and industry at large about the type of insights and data that is most important to their businesses. Our learnings were presented in this white paper and have also served as the basis of our own transparency-centered offering.

For us, transparency begins right here. The following explores exactly what’s on the table with CLARITY - myThings’ advanced analytics dashboard.

OPENING THE BLACK BOX

March 2014