Shopping doesn’t end with the holidays, and neither does competition in the retail space. To keep their numbers up, retailers have to keep shoppers flowing into the store (online or otherwise). We recently spotlighted remarketing as a successful tactic to achieve this goal. This time, let’s talk about lookalike modeling and contextual targeting.  Lookalike modeling can be used very effectively to prospect and drive new shoppers into the funnel. Contextual targeting refers to aligning advertising with content to increase the relevance of the advertising and ideally, advertising performance.

Lookalikes

Lookalike modeling is one of the best ways to put “big data” to work and drive new customer acquisition. Pulling data from first party data sets – POS, transaction, loyalty data or online behaviors – and combining that with other data on these consumers can create a detailed picture of who your best customers are across categories.  With this information, marketers can create detailed profiles of each type of shopper.  These profiles may include attributes like shopping behavior, product affinities, price sensitivities, devices used for shopping, and more.   These profiles can then be used to target audiences with similar attributes – audiences that “look like” and “behave like” your best customers.

It’s important to note that the term “look-alike” often means different things to different people.  On one end of the spectrum it can mean running a simple overlap report where you examine the packaged 3rd party data segments that over-Index the highest against your online “converters” or your best customers via your offline data set.  A true look-alike modeled segment uses predictive algorithms to identify the unique attributes of a consumer group (pre-packaged targeting segments might include dozens of attributes).   And to add even more complexity, the MediaMath “brain” – our decisioning algorithm – is really a model, determining the unique media characteristics and scenarios that are more predictive of your desired outcome.  Let’s take a look at each of these options.

• Segment Overlap Reports

When a marketer is trying to reach a specific, yet finite audience, segment overlap reports can offer a quick, potentially cost-effective way to expand reach.  These reports examine any online audience – an online converter (that might be aligned to a lower-funnel marketing tactic) or a homepage visitor (which might align more appropriately with a prospecting/upper-funnel tactic).  In either case, marketers may want to find more people “like” that in an effort to acquire incremental customers.  All platforms offer some sort of “Overlap report” that leverage pre-packaged segments from 3rd party data providers like eXelate, BlueKai, etc..  The downside to this option is that it is not a very precise method by which to identify unique audience attributes – the segments are a pre-packaged group of multiple attributes so it is absolutely a “broad stroke” approach.  That said, it is easy to implement and depending on what the overlap analysis says, it can be very cost effective.  For example, if the overlap analysis shows that your best customers are Moms with young children who enjoy NFL football, you can easily add contextual targeting to a buy or simply focus in on specific sites that reflect this audience or create whitelists that align with these audiences.  Buying the 3rd party data segments themselves is also an option, but might be cost prohibitive based on the campaign goal.

Upside: can be cost effective & easily to implement

Downside: less precise

• Modeled Segments

Marketers can also leverage data companies like eXelate or AddThis to create true look-alike models that use complex predictive algorithms to identify very granular attributes & combinations of attributes that uniquely identify an audience the marketer is trying to replicate at scale.  These companies have a tremendous amount of data that they piece together into targeting segments.  But they can also use the individual data components that make up a segment to create modeled audiences that are more precise and therefore (hopefully) drive stronger performance.  This option can also help marketers better understand their best customers and how they differ from other targets, hence making the entire media planning and targeting process smarter for current & future campaigns.  In some cases, the biggest downside to this option is cost – depending on the campaign goal, adding a $1-2 data CPM on top of media costs can be prohibitive.  But if the performance is high enough, the incremental cost is neutralized.

Upside: more precise

Downside: often require a minimum spend commitment which means optimizing away from this tactic if it’s not working isn’t an option

• MediaMath “Brain”

The “brain” is MediaMath’s machine-based decision algorithm that decides when to bid on an impression opportunity and what value to associate with that impression.  It ingests a marketers campaign goal (sales, enrollments, downloads, application completes, etc.) and identifies the unique media characteristics that tend to result in that “conversion”.  It then makes future bids decisions based on that information and continues to learn overtime as more conversions come in.    While it’s not a look-alike product, the MediaMath brain is a predictive model that examines 20+ variables at once to optimizes a campaign run through the MediaMath platform in an automated fashion.

Upside: easy to implement, always on option to optimize campaigns, no incremental cost

Downside: NO DOWNSIDE!

Marketers looking to identify incremental consumers in a manner that is smarter than the “spray and pray” approach can leverage “look-alikes” via a programmatic marketing operating system like MediaMath’s T1 to reach these consumers at scale.

Contextual Targeting – A Perfect Compliment

Contextual targeting can lead to better campaign results as ads are viewed as less intrusive given their high relevance to adjacent content. This targeting tactic is also cost effective which also lends to success.  A classic and simple example would be showing a shopper yoga pants as she’s reading an article about perfecting her warrior pose. She’s already thinking about yoga, so she’s likely to at least be interested in the yoga pants. Similarly, if a consumer is reading about the latest innovations in audio technology, new headphones might be really appealing.   Contextual targeting is not “intent-targeting” – these folks have not necessarily expressed their intent to buy a product via a search or product site visit – but it can represent an opportunity to drive better performance as you reach consumers while they’re in the right “mindset”.   Note that the best contextual tools will ensure that they’re relevant in a good way – so the ad for headphones doesn’t appear adjacent to content about the dangers of listening to music at high volumes.

Another highly valuable use of Contextual targeting is to define an advertiser’s brand safety policy – to some advertisers, celebrity gossip isn’t brand safe, but to others this is the perfect environment.  Other options available via Contextual targeting include:  showing up on pages with only 1-3 ad spots, high-visibility units, and those sites less likely to attract fraud.

Contextual targeting and lookalike modeling offer retailers a valuable method to reach shoppers in a smarter way – while they’re consuming relevant content or because they possess similar audience or media attributes as a group of consumers that have already proved themselves valuable to the retailer.

Ultimately, the beauty of the MediaMath platform is that you can test multiple targeting tactics like these to see what works best for your brand and then quickly and easily shift budgets toward the strategies that are working best.

To learn more about MediaMath’s solution, click here, and get more details about our retail capability here.

“The Click”

With click-through rates (CTRs) clocking in at a fraction of 1% at best, we know that they are not the best metrics to measure the success of campaigns.  Otherwise, we would accept the fallacy that 99 percent or more of our marketing dollars have no effect on consumers and are wasted spend.  But the CTR is like the “easy button” – it’s easy to track, easy to report.  I worked at DoubleClick in the early days of online advertising, so I take some credit for promoting this metric as the end all/be all. That was fifteen years ago, and today we’re smarter marketers with smarter technologies that allow us to better measure the efficacy of our advertising.

The idea that the last click should somehow get all of the glory would imply that the first four exposures in a campaign with an average frequency of five had no impact, or that 80 percent of our impressions and 80 percent of our spend was worthless.  Logically, we know this isn’t the case, but the “easy button” reporting systems often facilitate our dependence on this metric.

Attribution companies offer marketers the ability to view the impact of all campaign exposures on a consumer and on that consumer’s behavior with regard to the brand.  This insight is critical to gain a comprehensive and transparent view of marketing performance.  The ingestion of this data into a platform like MediaMath’s TerminalOne allows our decisioning algorithms to consider additional attributes when determining whether to bid on an impression and the value of that impression to a marketer.

Moving beyond the click to a more fractional attribution approach not only allows marketers to understand the media scenarios that yield the best results, but – supported by a technology platform – to activate against that data.

Full-funnel approach

Remarketing is a retailer’s best friend. It delivers measurable sales lift at a high ROI.  And why wouldn’t it be effective? Remarketing simply reminds folks of what they already know: they want to buy that sweater (or TV, or toy, etc.) they’ve been considering on your site.  It’s a tremendously successful tactic to get consumers over the finish line and secure the sale.  For retailers, that results in higher site conversion rates, more orders, and higher revenue.  Awesome!

What marketers often lose sight of, though, is that they need to employ upper funnel digital marketing tactics to drive awareness and consideration of their brand to attract more website visitors. (This is with the understanding that the vast majority won’t click on that ad to get to the web site, although they may visit later. You’re staying top of mind!)

The idea of keeping the funnel “full” is critical when you realize that a remarketing pool is only composed of the shoppers that have actually landed on your site. That’s a limited number of visitors! Digital media offers a unique opportunity to get your message and brand in front of a whole lot of eyeballs in a cost effective way, adding more shoppers to the top of the funnel and keeping the remarketing pool full of new customers rather than simply delivering your message to the same folks over and over again.

Going Beyond the Last Click

Employing prospecting tactics that leverage digital media will build awareness and consideration – and ultimately grow your remarketing pool.  Building your remarketing pool is a crazy-successful way to increase conversions. But what happens if you do this, and then use last-click attribution as your performance measurement strategy?  Your campaigns will be just as successful, but you’ll be giving ALL of the credit to the remarketing tactic. That could result in a reduced budget for prospecting because it’s not “performing”.

The best way to prevent this from happening is to identify goals per tactic. Prospecting will never perform like remarketing; it’s not supposed to.  The goal of prospecting is to bring new (incremental) consumers to your site, adding them to the pool. Then the remarketing campaigns can do the heavy lifting, reminding shoppers that they’ve been considering a purchase and still need to pull the trigger.

Learn more about MediaMath’s Retail capability.

The results are in and it’s official: People are shopping. A lot. That’s not so different from past Black Friday/Cyber Monday/ Cyber Week results – this has been the biggest shopping week of the year since Shop.org introduced Cyber Monday/Week.  But this holiday shopping season kickoff may be remembered for a few unique reasons:

Weaker Black Friday: The New York Times reported that Black Friday results were disappointing, but the low numbers may have been due to a “Black November.” Given the shorter shopping period this year, sales for holiday shoppers began as early as November 1. That and Thanksgiving Day sales may have eaten into Friday. All that said, the NRF reports that the number of shoppers was up, but the dollar amount spent ($407 per person) was lower than last year.

Strongest Cyber Monday on Record: Internet Retailer reported that $2.29 billion was spent on Cyber Monday, shattering all historical records. Business Insider estimates that total e-commerce grew 24% over the three key shopping days. ChannelAdvisor attributes part of this growth to shoppers scouring online stores for products that were sold out in-store. Also, where Cyber Monday used to be shop-at-work event, shopping this year extended well into the evening hours.

Now what? With just a week until Christmas how can retailers continue to drive sales? Regardless of how much has been spent, there are still plenty of shoppers with gifts left to purchase. What can be done to make sure those shoppers spend with you?

1. Activate display to compliment your direct mail strategies: By supplementing direct mail (the many catalogs, with carefully targeted display, retailers are sure to drive more shoppers into the store.  Email combined with direct mail and targeted, cross-screen display can be an incredibly powerful combination. Test the combination to see how it compares to other tactics.

2. Better leverage your offline data influence your online strategies: Beyond activating your CRM data to target high value customers, review store data to see which are most successful and which are struggling.  For the stores that are lagging in sales, invest in targeted display to drive in-store sales. Leverage your data to determine which products are most popular in which stores, then geo-target audiences to promote those products locally.

3. The shopping season isn’t over yet! So don’t just remarket – actively prospect! Use your data to create lookalike models that will help identify new audiences, then present them with relevant offers that will drive sales – continue to feed the funnel. Get incremental; get new users. Tailor your daily spend to mirror your anticipated revenues.

It may not be Cyber Monday again, but shoppers are still out there.

Food For Thought: How are you ramping up your spend to amplify shopping results? Learn more about how MediaMath’s Retail capability can help.

To learn more about MediaMath’s solution, click here.

As data becomes more prevalent in digital advertising, the ability to speak to consumers in an individualized way – and do that at scale — becomes a more valuable tool in the retailer’s toolkit.

Personalization in email is actually expected these days. A recent Responsys study revealed 61 percent of consumers feel more positive toward personalized email. Is that because email is considered a personal and private medium, and since it’s completely permission-based, there’s an implicit relationship between the sender and recipient?

If that’s the case, establishing that relationship across all marketing efforts should be a goal of retail marketers. eMarketer revealed that, per another Responsys survey, despite the “creepy” factor, 36% of consumers were interested in personalized display ads. The level of personalization may vary from advertiser to advertiser, but during the critical month of December, retailers might consider product recommendations based on consumer habits, their behaviors and their life stage to deliver more relevant messages and stronger performance.

Many retailers currently limit their personalization to location – which is a great start. This holiday season, shoppers in Albany may happily purchase down parkas and infinity scarves for their loved ones, but these gifts won’t be nearly as popular in Miami. Even the background image on an ad can impact customer sentiment: an alteration as simple as showing the New York skyline to a New Yorker or the Chicago skyline to a Chicagoan can have a positive impact.

Retargeting, of course, is a tried and true method of 1:1 marketing, favored by retailers and agencies alike to keep shoppers engaged even after they’ve left the online store.  Many will also leverage remarketing tactics using dynamic creative based on shoppers’ onsite behavior. This ability to put the right message/product before the right consumer is one of advertising’s silver bullets. Dynamic creative retargeting can move the needle quickly and efficiently as shopping deadlines approach.

Retailers seek to communicate with prospects in a more personalized way.  While remarketing often gets the accolades because of its strong performance, these are folks who have already expressed an interest in your brand by visiting your site.  But what about everyone else?  More relevant media via prospecting campaigns serves not only to fill the sales funnel (and build bigger remarketing pools)but also serves to speed up the consumer’s journey through the funnel as you deliver the right message at the right time.

What well-executed personalization yields, regardless of which tactics marketers choose, is the feeling of a one-to-one conversation. When a shopper sees an ad for a product they want, and sees that it’s on sale and in stock at their local Sears store (for example), a relationship has been strengthened. Sears knows that they want that item, and they’ve made it as convenient as possible for the consumer to purchase it. Sears has become the helpful shopping partner.

Programmatic technology not only helps marketers leverage and apply the data they need to facilitate customized advertising messages, it helps do this at scale.  And the impact and importance of this is something we can’t underestimate; when marketing efforts are personalized, the resulting campaigns feel like one-to-one communications. That’s immeasurably valuable. When consumers feel that a retailer understands their world, their needs, their purchase behavior and can create offers and experiences that are tailored to them, that’s powerful stuff. Not only are consumers more likely to purchase, they’re more likely to become lifetime customers.

A lesser known, or at least lesser-discussed, advantage of programmatic is that advertisers can use programmatic data to determine how much they’re willing to pay for each prospect. For example, a store like Babies “R” Us will likely bid more for new and expectant mothers, since those are their most valuable prospects.

So, programmatic makes it easier to identify, segment and target audiences with the right message at the right time, and pay a fair price for those audiences. It gives retailers the ability to do this in real time, helping drive the results they crave now, before the shopping season ends. And engaging customers on a one-to-one basis will not only help increase sales now, it will build relationships that benefit the retailer and the shopper all year long.

Food For Thought: What are you doing to build one to one relationships with your shoppers this holiday season? Learn more about how MediaMath’s Retail capability can help.

To learn more about MediaMath’s solution, click here.

The holiday shopping season has officially begun – although for many retailers, it began in early November. Opportunistic retailers began their sales early to capitalize both on the shortest shopping period in a decade and the early arrival of Hanukkah.

So with sales now in full swing, here are – in our estimation – the greatest Black Friday success stories of 2013:

Overall Success: Walmart is sure to win the shopping week, if not the whole month, based on its smart strategies this season. The retailer began its Black Friday deals both online and in-store early in the month, as early as November 10. Walmart also wisely revived last year’s “Guaranteed In Stock” hourly offers with even bigger and better deals, including featuring iPad prices. These offers commenced on Thanksgiving night, which stirred some controversy, and continued throughout Black Friday. Combined with buy online/pick up in store shopping options, as well as same-day shipping, and price-match guarantees, Walmart has all its holiday shopping bases covered.

Omnichannel Success: Macy’s and Target have proven that they understand how consumers shop today by embracing fully multichannel strategies this holiday season. With multi-channel holiday campaigns, multiple shipping and pickup options and smart mobile apps, these retailers are making shopping as easy as possible for customers, no matter how they prefer to shop.

Etailer Success: Amazon, as always, wins. With consistently lower prices, combined with exceptional use of customer data, Amazon is always able to offer clients the lowest prices on the products they actually want. Multiple shipping options and holiday deals give the online giant even more of an edge. Additionally, they win with the etailer advantage of 24/7, crowd-free shopping access, whether its Thanksgiving Day or Black Friday.

Viral Success: Kmart made some waves with “Ship My Pants” and “Big Gas Savings” earlier this year on YouTube. The retailer is ending the year with a bang (and a bump and grind) with their viral “Show Your Joe” video, promoting Joe Boxer shorts. The cheeky video has garnered over 14 million views in under two weeks, and has definitely helped the struggling retailer gain some mind share over the holiday season. We’ll see how that translates into sales.

Mobile Success: There are a few winners in this category for 2013. Both Target and Macy’s win here for their well-timed holiday shopping apps. By helping shoppers find both valuable offers and easily access product information, they two omni-channel winners can also add a mobile trophy to their shelves. Walmart earns kudos here, too: A recently-launched app enhances the in-store shopping experience by allowing consumers to purchase items that may not be available on the floor. So if the Hello Kitty pajamas your daughter wants aren’t available in her size in-store, they can be ordered in the right size via the app. The app, using location data, also helps customers locate items within the retailer’s giant stores.

FOOD FOR THOUGHT: What innovations did you incorporate this year to make shopping experiences seamless for your customers? Learn more about how MediaMath’s Retail capability can help.

To learn more about MediaMath’s solution, click here.