(Watch) I joined Ryan Joe, AdExchanger Senior Editor, to talk about Salesforce’s acquisition of Krux and how Salesforce is thinking about artificial intelligence, the role of data management, and applications for better marketing.
How Beacons Might Alter The Data Balance Between Manufacturers And Retailers
As Salesforce integrates DMP Krux, Chris O’Hara considers how proximity-based personalization will complement access to first-party data. For one thing, imagine how coffeemakers could form the basis of the greatest OOH ad network.
For years, marketers have been talking about building a bridge between their existing customers, and the potential or yet-to-be-known customer.
Until recently, the two have rarely been connected. Agencies have separate marketing technology, data and analytics groups. Marketers themselves are often separated organizationally between “CRM” and “media” teams – sometimes even by a separate P&L.
Of course, there is a clearer dividing line between marketing tech and ad tech: personally identifiable information, or PII. Marketers today have two different types of data, from different places, with different rules dictating how it can be used.
In some ways, it has been natural for these two marketing disciplines to be separated, and some vendors have made a solid business from the work necessary to bridge PII data with web identifiers so people can be “onboarded” into cookies.
After all, marketers are interested in people, from the very top of the funnel when they visit a website as an anonymous visitor, all the way down the bottom of the funnel, after they are registered as a customer and we want to make them a brand advocate.
It would be great — magic even — if we could accurately understand our customers all the way through their various journeys (the fabled “360-degree view” of the customer) and give them the right message, at the right place and time. The combination of a strong CRM system and an enterprise data management platform (DMP) brings these two worlds together.
Much of this work is happening today, but it’s challenging with lots of ID matching, onboarding, and trying to connect systems that don’t ordinarily talk to one another. However, when CRM and DMP truly come together, it works.
What are some use cases?
Targeting people who haven’t opened an email
You might be one of those people who don’t open or engage with every promotional email in your inbox, or uses a smart filter to capture all of the marketing messages you receive every month.
To an email marketer, these people represent a big chunk of their database. Email is without a doubt the one of the most effective digital marketing channels, even though as few as 5% of people who engage are active buyers. It’s also relatively fairly straightforward way to predict return on advertising spend, based on historical open and conversion rates.
The connection between CRM and DMP enables the marketer to reach the 95% of their database everywhere else on the web, by connecting that (anonymized) email ID to the larger digital ecosystem: places like Facebook, Google, Twitter, advertising exchanges, and even premium publishers.
Understanding where the non-engaged email users are spending their time on the web, what they like, their behavior, income and buying habits is all now possible. The marketer has the “known” view of this customer from their CRM, but can also utilise vast sets of data to enrich their profile, and better engage them across the web.
Combining commerce and service data for journeys and sequencing
When we think of the customer journey, it gets complicated quickly. A typical ad campaign may feature thousands of websites, multiple creatives, different channels, a variety of different ad sizes and placements, delivery at different times of day and more.
When you map these variables against a few dozen audience segments, the combinatorial values get into numbers with a lot of zeros on the end. In other words, the typical campaign may have hundreds of millions of activities — and tens of millions of different ways a customer goes from an initial brand exposure all the way through to a purchase and the becoming a brand advocate.
How can you automatically discover the top 10 performing journeys?
Understanding which channels go together, and which sequences work best, can add up to tremendous lift for marketers.
For example, a media and entertainment company promoting a new show recently discovered that doing display advertising all week and then targeting the same people with a mobile “watch it tonight” message on the night of it aired produced a 20% lift in tune-in compared to display alone. Channel mix and sequencing work.
And that’s just the tip of the iceberg — we are only talking about web data.
What if you could look at a customer journey and find out that the call-to-action message resonated 20% higher one week after a purchase?
A pizza chain that tracks orders in its CRM system can start to understand the cadence of delivery (e.g. Thursday night is “pizza night” for the Johnson family) and map its display efforts to the right delivery frequency, ensuring the Johnsons receive targeted ads during the week, and a mobile coupon offer on Thursday afternoon, when it’s time to order.
How about a customer that has called and complained about a missed delivery, or a bad product experience? It’s probably a terrible idea to try and deliver a new product message when they have an outstanding customer ticket open. Those people can be suppressed from active campaigns, freeing up funds for attracting net new customers.
There are a lot of obvious use cases that come to mind when CRM data and web behavioral data is aligned at the people level. It’s simple stuff, but it works.
As marketers, we find ourselves seeking more and more precise targeting but, half the time, knowing when not to send a message is the more effective action.
As we start to see more seamless connections between CRM (existing customers) and DMPs (potential new customers), we imagine a world in which artificial intelligence can manage the cadence and sequence of messages based on all of the data — not just a subset of cookies, or email open rate.
As the organizational and technological barriers between CRM and DMP break down, we are seeing the next phase of what Gartner says is the “marketing hub” of interconnected systems or “stacks” where all of the different signals from current and potential customers come together to provide that 360-degree customer view.
It’s a great time to be a data-driven marketer!
Chris O’Hara is the head of global marketing for Krux, the Salesforce data management platform.
Salesforce unveiled its Einstein AI platform this year, baking predictive algorithms, machine and deep learning, as well as other data analysis features throughout its Software-as-a-Service (SaaS) cloud. Einstein is essentially an AI layer between the data infrastructure underneath and the Salesforce apps and services on top. The CRM giant is no stranger to big money acquisitions, most recently scooping up Demandware for $2.8 billion and making a play for LinkedIn before Microsoft acquired it. The Krux acquisition gives Salesforce a new, data-driven customer engagement vector.
“We’re working to apply AI to all our applications,” said Eric Stahl, Senior Vice President of Marketing Cloud. “In Marketing Cloud, Krux now gives us the ability to do things like predictive journeys to help the marketer figure out which products to recommend. We can do complex segmentation, inject audiences into various ad networks, and do large-scale advertising informed by Sales Cloud and Service Cloud data.”
As Salesforce and Krux representatives demonstrated Krux and how it fits into the Marketing Cloud, the data management platform acted more like a business intelligence (BI) or data visualization tool than a CRM or marketing platform. Chris O’Hara, head of Global Data Strategy at Krux, talked about the massive quantities of data the platform manages, including an on-demand analytics environment of 20 petabytes (PB)—the entire internet archive is only 15 PB.
“This is our idea of democratizing data for business users who don’t have a PhD in data science,” said O’Hara. You can use Krux machine-learned segments to find out something you don’t know about your audience, or do a pattern analysis [screenshot above] to understand the attributes of those users that correlate greatly. We’re hoping to use those kinds of signals to power Einstein and do things like user scoring and propensity modeling.
The Einstein Journey Insights feature is designed to analyze “hundreds of millions of data points” to identify an optimal customer conversion path. In addition to its Krux-powered Marketing Cloud features, Salesforce also announced a new conversational messaging service called LiveMessage this week for its Salesforce Service Cloud. LiveMessage integrates SMS text and Facebook Messenger with the Service Cloud console for interactions between customers and a company’s helpdesk bots.
The more intriguing implications here are what Salesforce might do with massively scaled data infrastructure like Krux beyond the initial integration. According to O’Hara, in addition to its analytics environment, Krux also processes more than more than 5 billion monthly CRM records and 4.5 million data capture events every minute, and maintains a native device graph of more than 3.5 billion active devices and browsers per month. Without getting into specifics, Salesforce’s Stahl said there will be far more cross-over between Krux data management and Einstein AI to come. In the data plus AI equation, the potential here is exponential scale.
A survey of both senior marketing and IT professionals has revealed that there are significant differences between these two core business functions in their perception of organizational priorities and the quality of digital infrastructure. Governance frameworks to ensure better alignment between the CMO and CIO are often lacking.
The Backbone of Digital report, freely available from ClickZ (registration required), has also found that, compared to their colleagues in marketing, IT professionals have a much rosier view of the customer experience their companies are delivering across digital channels.
Below I have outlined more detail around three key findings from the research which is sponsored by communications infrastructure services company Zayo.
IT pros have exaggerated view of the quality of their companies’ current infrastructure
According to the research, 88% of IT respondents describe their company’s infrastructure as ‘cutting-edge’ or ‘good’, compared to only 61% of marketing-focused respondents, a massive difference of 27 percentage points.
The research also looks at the ability of tech infrastructure to deliver across a range of marketing communications channels, with IT respondents and marketers both asked to rate performance.
Both marketers and IT professionals felt that the best engagement and experience is delivered across desktop, cited as ‘excellent’ or ‘good’ by 71% and 93% of these groups respectively, but trailed by other channels including mobile website, mobile app, desktop display, mobile display, social and push messaging.
Across the board it is evident that those working in IT have a much more optimistic view of how well they are delivering across the full gamut of digital channels compared to their IT counterparts.
It seems likely that those working in more customer-facing departments, i.e. marketers (generally), are much more likely to be aware of deficiencies impacting customer experience which can adversely affect business performance and brand reputation (and often their own bonuses).
A lack of co-operation is undermining excellence in digital delivery
Just 19% of marketers strongly agree with the statement “marketing and IT work closely together to ensure the best possible delivery of product/service”, and only 11% strongly agreed that they “have a clear governance framework to ensure that CIOs/CTOs and CMOs work together effectively”, suggesting a lack of alignment around marketing and IT business objectives.
This compares to 45% of IT professionals who strongly agreed that “marketing and IT work closely together to ensure the best possible network performance”, and a similar percentage (46%) who strongly agreed that they “have a clear governance framework to ensure that front-end business applications and back-end infrastructure work together effectively”.
While there are differing perceptions about the extent of marketing and IT co-operation, the report concludes that business objectives need to be much better aligned to ensure closer harmony across these core business functions. If a framework to facilitate this is not put in place at the top of the organization, it becomes exponentially more difficult to implement lower down.
Speed of data-processing is crucial – real-time means real-time
Marketers are increasingly aware that the proliferation of data sources at their disposal is only of use to their businesses if they can analyse that information at high speed and transform it into the kind of intelligence that can then manifest itself as the most relevant and personalized messaging or call to action for any given site visitor.
According to Mike Plimsoll, Product and Industry Marketing Director at Adobe:
“A couple of years ago the marketing leaders at our biggest clients typically expected that data could be processed within 24 hours and that was fine.
“Now when we talk to our clients the expectation is that data is processed instantly so that when, for example, a customer engages with them on the website, the offer has been instantly updated based on something they’ve just done on another channel. All of a sudden ‘real-time’ really does mean ‘real-time’.”
The ability to harness ‘big data’ has become a pressing concern for IT departments as their colleagues in marketing departments seek to ensure they can take advantage of both structured and unstructured data and ensure the requisite speeds for real-time optimization of targeting, messaging and pricing.
More than half of IT respondents (56%) said that the ability to manage and optimize for big data was currently a ‘very relevant’ topic for their organization, in addition to 37% who said it was ‘quite relevant’.
According to Chris O’Hara, Head of Global Data Strategy at Krux Digital:
“Today, consumers that are used to perfect product recommendations from Amazon and movie recommendations from Netflix expect their online experiences to be personal, email messages to be relevant, and web experiences customized.
“Delivering good customer experience has the dual effect of increasing sales lift, and also reducing churn by keeping customers happy. Things like latency, performance, and data management are all part and parcel of delivering on that concept.”
Please download our Backbone of Digital research which, as well as a survey of marketing and IT professionals, is also based on in-depth interviews with senior executives at a number of well known organizations.