Hello, all, and here’s to a promising 2017!
As most of you know, I had a big change in 2016. After creating, building, and leading the Oracle Marketing Cloud from obscurity to industry leadership for the last 3 years, which was a beyond-amazing career experience (thank you Oracle!), I made the exciting move in August to assume the role of CEO for Cision, a global top-15 SaaS company that is about to do many of the same things for Earned media that OMC (and Adobe, Salesforce, IBM Marketing Clouds as well) are doing for Paid and Owned media.
So, the last five months of the year, I’ve published, blogged, tweeted, posted, emailed, key-noted, panel spoken, commented, and so forth a lot on this exciting new transition. This has included a lot of forward-looking trends and thought leadership specific to Earned Media and Communications going through this data, technology, and measurement transformation specifically.
However, when the good folks at Leadspace invited me to guest blog — as they have for years, for which I am always honored — on the broader “most exciting Marketing Technology trends in 2017” topic, I was happy to opine on the broader Marketing and Ad Tech sector.
So, happy new year, and here are some of my thoughts on what we’ll see as priorities for adoption and investment in 2017.
Category #1: Real-time data technologies
The intersection of data and applications and/or media has never been more important, and will reach an all-time high in investment and implementation in 2017.
While this is a broad category, with lots of noise, hype, and fairy dust swirling, there are a few major categories that I believe are the most important to track (and if you’re an aspiring digital CMO and haven’t made these investments, it’s time to start talking to the CIO and the CFO about making them).
Real-time content/offer management. Whether it’s dynamic creative optimization (DCO), digital ad buying, website or mobile app personalization, digital commerce product or offer optimization, or trigger-based (such as omni-channel re-targeting, real-time location marketing, and many more), this iceberg we’ve only scratched the surface of will be at the top of the list as far as importance. The sophistication level is still barely past nascent, while the business impact of harnessing data and using it in real-time to fuel customer experience, conversion, purchase, etc., across this wide array of applications is massive.
Real-time data enrichment. Data is the fuel that makes everything else run. The more robust, enriched the data, the better the applications or media that are consuming it perform. It’s beautiful when it’s that simple, and this one is.
The real-time CRM and Marketing Automation data vendors (including Leadspace) should have another big year based on the growing acknowledgement that this type of service dramatically enhances the performance of these massive CRM and MA investments companies have made.
While there are marginal performance/ROI improvements in the feature/function innovation in the software containers, there is huge performance/ROI improvement to be had by fueling the apps with better/more enriched data upon which they can do all the real-time automated stuff — as well as the more core, day in and day out lead and opportunity management and nurturing functions they are vital for.
This is most commonly known as “predictive”, which I think is accurate at this point. We can and should also say “responsive”, as that is what the biggest bang for the buck is. Enrich the data in real-time, and know how to RESPOND to the data signals in real time. Only 10% of the marketers out there are even doing this as common practice right now, and we should see a lot more adoption this year.
I put the “AI for marketing” and “Machine Learning for Marketing” in this category for 2017. These will sophisticate and be their own category in the not-too-distant future, but for now, the market isn’t even doing the basic blocking and tackling when it comes time to letting the data be captured and reacted to in real time along simple, but effective, programs and methodologies.
DMP becomes mainstream, and not just for ad buying. Why did Oracle, Adobe, Salesforce.com, Neustar, Neilsen all pay top dollar the last few years to acquire leading DMP technology companies? Because the DMP is a core customer data and actionable audience profile technology that is requisite to do digital, data-driven, real-time marketing and advertising of all flavors.
We will never be able to satisfy the requirements with Enterprise Data Warehousing 3.0 or 4.0 or 5.0, nor with re-tooled data-marts, nor with Master Data Management (MDM). The ability to manage dozens of digital IDs, thousands of datasets, in the cloud, integrated into the marketing and advertising applications to enable real-time action and response, is the new table stakes — and that’s the DMP.
DMPs will begin to fuel commerce, CRM, marketing automation, campaign management, and other applications across the whole customer lifecycle as well — not just the paid advertising optimization they’ve been utilized in for the first half of this decade.
You’ll notice I didn’t put “Big Data” here.
“Big Data” continues to be an amorphous, generic, catch-all phrase as applied to Marketing and Advertising. Getting the RIGHT data, in real-time, and ACTIONING it is what’s important, not “MORE” or “BIG” data.
I believe we’ll see a lot more CMO’s surface out of the hype quagmire, realize this, and invest and adopt practical data acquisition, integration, enrichment, and actionability strategies as their priority in 2017.
Category #2: Identity Management
If we want to achieve omni-channel – or x-device; or seamless customer lifecycle from awareness to advocacy; or any of the other aspirational goals we’ve been putting on this list for the last 2 decades, and still have yet to accomplish — the foundational step is IDENTITY.
The normal digital customer (be it B2B or B2C) has over a dozen identities now – multiple emails, multiple device IDs, multiple social IDs, multiple cookie sets, multiple CRM, commerce, marketing automation, or other “software IDs”, multiple Ad IDs, etc. And that’s before you get to the Google, FB, Amazon, MSFT, Verizon, … IDs.
If you can’t reconcile these identities into one ACTIONABLE profile for your customer or prospect (and to be factual, one anonymous profile and one ‘known’ profile for privacy and data usage legislation reasons, but I won’t geek out too hard on that in this piece) back into all these digital channels in real or near real-time, this will continue to be the great Unicorn. We read about it, see movies on it, but it’s not real yet.
Until Identity Management is adopted so that the one “Kevin Akeroyd” profile exists across my many offline, digital, social, mobile channels, devices, and media, we’re still talking about a mythical creature not a real one.
You’ll see the data players like Acxiom and Experian (Acxiom is doing very interesting things with the LiveRamp acquisition and their vast offline data-sets); and the technology companies like Oracle, Adobe, IBM, and Salesforce.com (Oracle’s Datalogix, Crosswise, BlueKai, and AddThis acquisitions has it in a really good leadership spot currently, but their competitors are bringing practical high-return, bite-size solutions to market fast so they need to stay nimble and fast); and the Digital Agencies (WPP, Publicis are the two biggest cats in the jungle here, and both announced very compelling data/identity solutions in 2016) be the emerging leaders on the vendor side.
On the Client side, I think you’ll see Financial Services, Retail, Travel, Auto, and believe it or not CPG lead the early adopters’ curve.
Category #3: The age of the Influencer
The age of the influencer (Earned media) is upon us – we can’t advertise (Paid media) or promotional campaign (Owned media) our way there.
While this sounds self-serving since I’m the CEO of the biggest Earned Media/Influencer platform in the industry, that aside, this is a very real trend and we’re going to see rapid transformation here. Why? Because every CMO in the land realizes that the efficacy of my advertising (and the QUALITY incremental reach I can continue to attain vs. just reach for reach’s sake is getting thin) will continue to decline.
Serving up 10 billion FB, Google, and Comcast impressions this year vs. 7 billion impressions last year simply isn’t gonna cut it. Neither is sending out 5 billion SMS, Push, and emails vs. 4 billion last year. The customer (again, whether B2B or B2C) simply is becoming de-sensitized and numb to these blatant media tactics. They just don’t trust, give credibility to (never mind loyalty, goodwill, or brand reputation to) the ad and promotional stuff like they used to.
What DO they trust? The INFLUENCERS. Peers. Journalists. Bloggers. Academics. Social entities. Communities. Fellow employees.
The CMO must figure out how to reach their customers via the influencers in an analytical, automated, data-driven way. That means they’re going to have to do the same data, technology, and measurement transformational investments in Earned media that they’ve already made in Paid and Owned. Once they do, they’ll be able to measure the impact, optimize it, and shift spend to the content, channels, and influencers they must figure out. And they’ll have to do it with a platform, not a bunch of point solutions (shameless Cision plug there!)
Category #4: Analytics rationalization, emergence of Attribution
We’ve got “Big Data”. MDM. Web analytics from Adobe or IBM or Web Methods. Mobile Analytics from Mix Panel or Localytics. Social Analytics for god-knows-how-many-players now. PR Analytics from Cision or Trendkite. Ad analytics from the networks themselves (Google, FB), the DSPs (display, search, video all disparate players), the 3rd party ad players (think Moat, IAS, comScore), offline analytics (Nielsen, Datalogix). We’ve got our enterprise analytics from IBM or Oracle or SAP or SAS. We’ve got our cloud data visualization analytics from Domo or Qlik or Tableau. We’ve got our predictive analytics. Our point-solution analytics off the back end of Exact Target or Responsys, Marketo or Eloqua.
We are now spending more time than ever synching disparate analytics systems. I believe a rationalization of core systems will continue to drive the consolidation of vendors and the consolidation of buyer spend (stacks vs. point solutions). And I believe Attribution (folks like Beckon, Origami, Datorama) that go beyond analytics in silos and get to actual attribution of KPIs driven by ad/marketing spend, so the CMO can optimize across the dozens-wide marketing and ad mix of channels and vendors, will see a major uptick in 2017 given the mission critical importance of doing this.
We’ll see whether the legacy Mix Modelers make the jump from Mix Modelling to SaaS Attribution providers. If that happens, the category will really heat up.
I could –and usually do – continue to opine, but I will stop here so you can get on with your New Year. Best of luck CMOs for a phenomenal 2017, and if you aren’t up to speed on the above, I recommend you get there, these are important!
Here’s a useful illustration of why predictive analytics made Kevin Akeroyd’s list of exciting martech to watch out for in 2017:
Kevin Akeroyd oversees the Cision executive management team across operations globally.
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