Content Marketing Series: Conversation with Woody Meachum, Group Director of Digital Strategy at OMD

Content Marketing Series: Conversation with Woody Meachum, Group Director of Digital Strategy at OMD

Bidtellect is excited to launch a new content series on our blog featuring industry thought leaders from brands, agencies and technology companies. They will explore the role of Native Advertising and Content Marketing in their marketing plans, and the latest trends and developments on the horizon.
For the first edition of the series, Bidtellect interviewed Woody Meachum, Group Director of Digital Strategy at OMD. Woody is responsible for the go-to-market digital strategy across the brand, acquisition, retention, cross-sell, recruitment and small business campaigns. Woody works closely with the agency’s programmatic department as his digital team takes a very strong programmatic approach to their GTM plans, whether it’s from an inventory perspective or managing DSP, DMP, and data partnerships.

What are some of the biggest challenges and concerns your clients face in Native Advertising and Content Marketing? What are some of the biggest opportunities?

One of the biggest challenges that we have right now is adjusting the thinking around how to bring content to market. Many marketers tend to develop and execute content strategies in a similar way to social, but while social and content marketing are similar, they also have many differences.
They can use similar assets but the consumer behavior is different. Part of the problem is getting people to understand that when consumers are on social they are in discovery mode – they are on a social platform because they are looking for something, whether it is an update on a family member, sports score etc. That is not always the case when a consumer is surfing on desktop or mobile web. In that case, it is more of a lean back activity. Instilling in marketers that the same asset can be judged differently depending on where someone is experiencing it is a major challenge.
Another obstacle lies with the technology. With so many partners entering the Native marketing space, I see the direction moving more and more toward programmatic environments. A lot of these Native networks are starting to become similar to the ad networks 8-9 years ago. For example, some of the bigger native providers are becoming more like the equivalent of, Yahoo, and MSN in the early 2000s that have exclusive partner relationships. The challenge comes with moving all this inventory into programmatic arenas so that we can access it through a DSP. Implementing more efficient workflow processes this way is critical, especially as we need to achieve scale with fewer partners versus having numerous direct site buys.
Although this is a major challenge facing the industry right now, it also speaks to the opportunity. The asset kit for Native campaigns becomes much easier for a creative agency to put together and then strategically plan for content calendars and sequencing. But perhaps the greatest opportunity for marketers is that content marketing allows the advertiser to join an existing conversation or start a new conversation that hasn’t been made available through traditional banner advertising.

How do you see Native Programmatic progressing in 2017?

To me it is one of the biggest possibilities of growth in 2017 because Native environments are what consumers are responding to. Although some Native units are similar to banners on the back end, the way that they are assembled, placed and designed they look and feel more like an article. Therefore, the blindness that people tend to experience with the regular 300X250 does not apply. You will see much higher engagement rates with these units. I specifically say engagement rate instead of CTR because someone is engaging with a piece of content. It’s a value exchange for the engagement. A person knows that when they engage with that piece of creative they are going to be consuming a piece of content versus clicking on a banner ad.

Do your clients already have a significant amount of content, or are they investing in creating more content?

Yes, they are creating on their own. There have been clients that have actually developed content teams within their organization since I’ve been working with them. Then there are other clients that already had it in place and just didn’t know it. They were producing all this quality content, but weren’t sure if they could take content being created internally and put it online.
Content strategy has become much more internal, versus hiring outside talent to create content for them. But these teams need to learn that for content marketing to work well it is no longer just writing one headline. A new type of behavior needs to be instilled. For example, when you write an article, write 5 headlines for it, when you select a picture to accompany an article, pick 5 potential options. It’s really important to focus on switching people’s behaviors on creation because in Native environments brands need to be able to message test.
However, external content partnerships will never go away. Brands gain credibility through alignment, but I see these being much more focused on-going relationships versus one-off “advertorial” deals.

And do clients understand the importance of then distributing that content?

Yes – it is such an important part. It has been crucial getting clients to think about the creation components, and then it is a big part of my job to think about the distribution component. This has required a change in the mindset of the media buyers. It’s a new way of thinking – what environments are these going to appear in? Will this placement be contextually relevant?

What is an example of Content Marketing done well that you have seen recently?

I had a financial client that was very resistant to content marketing for anything but branding. When I suggested incorporating it into their plan to generate leads for signing up for new accounts, they weren’t sure that people would respond. I explained to them that people want to learn, so if you distribute an article titled “5 things you need to look for when you’re opening a checking account,” there is a good chance that someone who engaged with and liked that article will be interested in signing up for a checking account with you. This is the same investment as putting together a rotating banner ad, but much more effective.
It turned out that the content marketing that we were running at the time ended up being the second-best performer on a 10 partner plan. The client liked it so much that when they added incremental budget the only thing we kept running was the content piece because it was the most efficient and engaging and brought a better quality customer.

How does Content Marketing fit into your clients’ overall marketing strategies?

Through my lens, content and Native are in the same bucket. Content is simply the asset that Native delivers and is a key component across all of our campaign areas. In terms of performance measurement, KPIs for content are often dependent upon the KPI of the campaign it is running within.
For brand campaigns, the main objective is engagement and getting consumers to interact with a piece of media. For acquisition campaigns, content is actually looked at from the same KPI, which is a cost per acquisition, as any other campaign in that category. For example, an article that is running through one of our programmatic Native partners is viewed in the same KPI structure as a banner ad or paid search. There are often different baselines of performance, but we are still looking at them from the same DR perspective because we see that different channels bring in a different type of consumer.
Any prospect that we bring in is looked at from a value perspective. We judge the quality of the lead that a campaign brings in, not just the efficiency of the media that we purchase.

What trends do you see on the horizon in Content Marketing and Native Advertising over the next 6-12 months?

We will see further integrations of content networks into overall programmatic buys so that they are viewed the same as a banner buy. This will enable us to have control over the reach and frequency. Also, sequential messaging with content will continue to be an area that we will explore.

Leveraging Fast and Efficient Optimization Technology in Smart Advertising

Leveraging Fast and Efficient Optimization Technology in Smart Advertising

Running effective campaigns that deliver results in a native demand side platform (nDSP) requires a sophisticated optimization strategy and a constant focus on innovation. The digital content and advertising environment can be crowded, so brand advertisers need to be confident that their media buys are relevant, precisely targeted and driving meaningful results for their business. For this reason, improving and advancing optimization algorithms and technology is a core focus at Bidtellect and has always been part of the company’s DNA, beginning with its roots at with Co-Founder John Ferber.

We are currently preparing to release the 4th generation of our optimization technology. This technology utilizes big data, predictive modeling and machine learning to intelligently analyze and bid on billions of impression opportunities every day.

There are a variety of objectives that campaigns are measured against, and each advertiser and each campaign define success differently. Through everything mentioned above, Bidtellect’s optimization platform is working throughout the life of a campaign to ensure it is maximizing the results of the chosen KPI. A unique advantage of Bidtellect’s technology is its ability to optimize toward multiple KPIs simultaneously.
While we offer over 10 KPIs for a buyer to optimize towards, we see tremendous value in the post-click metrics. For example, Engagement Score, bounce rate, time on site, etc. Post-click activity will become increasingly critical for marketers as they seek more meaningful ways to determine how consumers are interacting with their content and brand.

According to comScore, Bidtellect reaches nearly 75% of the entire US market on over 10 million placements via real-time bidding. At scale, optimization technology is vitally important in considering not only where to buy, but when to do so and for how much. Machine Learning is key to the estimation of the KPIs and is where predictions meet learned results to continually refine a campaign from the day it is launched. It is typical and expected to see KPIs improve steadily throughout a flight.

The below process summarizes the workflow:
Step 1: Receive Impression Request:
We see a constant stream of supply of billions of opportunities each day that we are able to bid into.

Step 2: Scrub Request:
Begin the process of analyzing the impression opportunity. Eliminate fraudulent inventory with the help of efficient it consulting services and ensure we understand the validity of the supply.

Step 3: Filter Ads by Inventory Targeting:
Match our advertisements and campaign requirements to the supply source and see if there is a match.

Step 4: Run Pacer:
Determine if there is enough money in the campaign to buy that opportunity. Helps ensure proper pacing and smooth delivery of campaign.

Step 5: Predict KPIs:
By employing advanced machine learning methods we are able to predict KPIs for an individual request using a large number of features of the user, page, and advertisement.

Step 6: Calculate Valuation Factors:
Given the KPI predictions, determine if the impression aligns with an advertiser’s goals.

Step 7: Calculate Bid:
Given the campaign’s base bid price, combine the valuation factor and base bid to obtain a final bid price expressed in effective CPM.

Step 8: Ad Selection:
Process of comparing effective CPM of multiple ads that you can possibly run there and determine the logical choice.

Step 9: Bid:
Place a bid on behalf of the campaign with the best-predicted outcome.

Although it is an extensive decision-making process, all of these steps are actually happening hundreds of thousands of times per second, which is key in the always-on real-time world that we live in. An individual transaction occurs start to end within 100 milliseconds. To compete you have to have a fast, smart and efficient optimization platform otherwise you will lose out on the opportunity.