Microsoft and Salesforce have announced plans to expand their strategic partnership through the migration of Salesforce’s Marketing Cloud to Microsoft Azure. The move is anticipated to allow Salesforce to optimize Marketing Cloud performance to meet increasing customer demands.
In order to support
their joint customers using Salesforce CRM and Microsoft Teams, Salesforce will
also build new integrations for its Sales and Service clouds with Teams. The
integrations will allow sales and service users to access Salesforce records directly
in Teams, and is expected to go live in late 2020.
Why we should care
Marketing Cloud to Azure will allow the company’s customers to benefit from
Azure’s infrastructure which will help brands manage data security, privacy and
compliance requirements on a global scale.
The integration between the widely-used Salesforce CRM and Microsoft Teams can be expected to drive further collaboration across sales and service teams by increasing accessibility to data directly within the Teams app. Salesforce and Microsoft customers – like Marriott International – will be able to take advantage of improved collaboration and greater efficiency through the strategic partnership.
“Marriott has more than 7,200 properties spanning 134 countries and territories, so driving efficiency and collaboration is critical,” said Brian King, global officer, digital, distribution, revenue strategy and global sales, Marriott International. “The combination of Salesforce and Microsoft enables our teams to work better together to enhance the guest experience at every touchpoint.”
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By bringing its Marketing Cloud to Azure, Salesforce joins over 95% of Fortune 500 companies using the Azure infrastructure, which covers the most global regions of any cloud provider.
“In a world where every company is becoming a digital company, we want to enable every customer and partner to build experiences on our leading platform,” said Satya Nadella, CEO of Microsoft. “By bringing together the power of Azure and Microsoft Teams with Salesforce, our aim is to help businesses harness the power of Microsoft Cloud to better serve customers.”
Performance marketing agency Merkle has released the latest edition of its quarterly report, the Q4 2019 Customer Engagement Report (download required). The report addresses results from a Merkle survey of over 200 marketers from North American brands spanning across industries including retail, high-tech, financial, travel, media and entertainment, health and nonprofit.
The Q4 report explores the various data types marketers use to enable personalization, along with the emerging tools and tactics that drive ongoing marketing improvements. The survey found that while there is broad adoption of personalization across marketing organizations, there is plenty of room for growth.
Why we should care
The survey discovered that 86% of marketers have the budget, solutions and infrastructure in place to drive personalized customer experience across digital channels. Despite having all the right tools, respondents indicated that the use of individual data sources for personalization is low. According to Merkle, 70% of respondents reported that third-party customer demographics are used in email, 40% in digital media, and less than 30% on website.
Merkle also analyzed loyalty program tactics used by marketers. The study found that despite respondents indicating an increase in investments in loyalty platforms and emerging technologies, spend on loyalty program management, email marketing and operational resources have stayed the same or decreased. 81% of survey respondents reported they have a defined loyalty program in place.
Additionally, Merkle identified a gap between high-level reporting on data use and available and the use of specific data sources for loyalty programs. 62% of respondents indicated they have loyalty programs that are fully integrated with their CRM data, but are using less of the available data in loyalty efforts compared to wider marketing initiatives; 38% indicate using third-party demographic data to personalize loyalty programs compared to 86% in overall marketing efforts.
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60% of respondents reported that a majority of their revenue was driven by data-based triggers but only 28% of messaging is based on one-to-one behavior triggers.
Nearly 90% of marketers use personalization on at least one channel, but most have not adopted advanced tactics.
Canadian e-commerce platform Shopify has announced the launch of its newest marketing app extension, Shopify Email. Shopify Email will allow Shopify merchants to create, execute and monitor email marketing campaigns natively within the platform. The new capabilities are expected to be generally available to Shopify merchants beginning in early 2020.
In 2018, Shopify launched Shopify Marketing as an all-in-one marketing solution for merchants on the platform. Shopify Email marks the platform’s next step towards making marketing tools more accessible to sellers. Emails can be sent from the merchant’s domain name, and require little technical setup.
Why we should care
The value of email for SMBs and should not be overlooked. As one of the highest-converting marketing channels, email is critical for establishing trust with customers. Adding email capabilities to its platform will enable Shopify merchants to manage their communications with their customers alongside their inventory, creating a streamlined system within the Shopify environment — while saving merchants the costs of investing in and integrating a third-party provider.
Shopify Email also includes campaign analytics to help users measure their email marketing campaigns with open and click-through rates, as well as insight into the products added to shopping carts and purchases. Merchants can take advantage of these to optimize their email marketing campaigns.
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Shopify Email provides customers with customizable email templates that can be used with existing brand assets and products.
Shopify has partnered with advertising platforms such as Facebook, Google, Microsoft and Snapchat.
Third-party marketing apps including Seguno, Omnisend and SMSBump have also integrated into the platform to allow for integrated, cross-channel marketing campaigns.
Customer data platform (CDP) Lytics announced updates to its platform that will allow users to integrate customer journey execution with Salesforce Marketing Cloud (SFMC). Lytics’ campaign orchestration capabilities can now be used across a number of marketing technologies, including Facebook and SendGrid – in addition to the new SFMC integration.
The integration between Lytics’ CDP and SFMC is expected to allow marketers to import existing campaigns to build new experiences within the Orchestrate Journey canvas. The insights delivered from Lytics can then be used to inform more targeted campaigns and be sent to SFMC for delivery.
Why we should care
Delivering personalized, one-to-one marketing at scale is something we strive for as marketers. Our disparate martech environments tend to complicate this, and customer data platforms seek to address these complications by providing users with a single view of their customer data from the different tools they use. Marrying this data into a single view should help marketers extract new insights to further inform their campaigns.
“The best customer journeys are an open road,” said James McDermott, CEO of Lytics, “and for us, that means giving marketers the freedom to choose multiple paths by integrating with their existing marketing technology stack.”
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With the new Lytics and Salesforce Marketing Cloud integration, users can:
Export audience segments from Lytics into SFMC to continue the customer journey
Trigger new experiences in SFMC based on customer events (e.g., opened an email) captured in Lytics
Switch between Lytics and SFMC within the same customer journey to deliver a combination of channel and message.
Email marketing platform SparkPost has announced plans to purchase reputation management, email deliverability and analytics provider eDataSource.
The acquisition is expected to provide SparkPost and eDataSource customers the combined abilities to create, send and measure email performance and inbox placement analytics. The announcement also included plans to launch new capabilities, including automatic seeding and real-time blacklist alerting.
Why we should care
Reaching the managed inbox continues to pose challenges for marketers. Deliverability is becoming increasingly complex, and email marketers often feel the negative impacts on their email marketing efforts every day. Many email service providers (ESPs) can give users insight into email performance based on metrics, but marketers often turn to third-party deliverability solutions to enhance placement and deliverability insights, and the upcoming merger seeks to address these challenges for its customers.
Integrating deliverability insights into the platform could have a strong impact on email marketers’ understanding of deliverability. With one in five emails never reaching the intended inbox, the integration between SparkPost and eDataSource could signal a coming change in how we can leverage martech and data to better understand and manage our relationships with subscribers.
understanding deliverability and inbox performance, customers will be able to
optimize their sending for improved engagement and business results from their
email,” said SparkPost CEO Rich Harris. “Deeply integrating sending
and analytics will provide richer insights and new capabilities like automatic
seeding, accurate weighting of inbox placement and blacklist impact based on
actual sending patterns.”
As consumers become increasingly aware of how personal data can be exchanged for value, their expectations from brand interactions are growing — especially for retail brands entering the holiday season.
According to a survey from customer data platform RedPoint Global, 75% of consumers said that they wish retailers understood their personal preferences better and would use those insights to inform future offers.
Why we should care
While the survey specifically focuses on the upcoming holiday shopping season, personalization is not a passing marketing trend. Nearly 60% of survey respondents indicated that they are more likely to purchase from retailers who send them personalized content and offers. With personalization driving conversions and sales, marketers should anticipate that consumer expectations are only going to climb higher when it comes to delivering the right offers.
“It’s clear that consumers have had enough of irrelevant communication from brands that fail to leverage personal preferences and engagement history,” said Redpoint Global chief marketing and strategy officer, John Nash. “Every buyer expects to be treated as a unique individual — and the holiday season is an ideal time for retailers to deliver on these preferences and win customers over.”
But in order for brands to deliver the personalized experience consumers crave, it’s important that marketers consider how consumer data fuels personalized offers. Nash explained, “To achieve long-term loyalty… retailers must build effective relationships with each unique customer across all touchpoints — not just during the holidays, but all year long.”
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Additional insights from the survey include:
74% of brand loyalty members expect brands to understand their needs and expectations better than other retailers where they are not a member.
Over a third of respondents remain loyal to their “go-to” brands for holiday shopping, saying they exclusively purchase from retailers that they have shopped with in the past.
Over a third of consumers surveyed said they made a holiday purchase on Amazon Prime Day in July 2019.
We’re 20 years into the SaaS revolution now, and B2B companies have gotten the table stakes of an operational set-up for tactical go-to-market pretty much down. We know how to define our ideal customer profiles (ICP) in terms of firmographics. We understand the importance of technographics and the implications of existing installs on sellability. We’ve learned about buying team dynamics and we’ve gotten the hang of creating personas to help us address the typical needs of important functions and roles. And, if we have enough historical data, we can now pretty easily use analytics to model propensity to buy, project that onto a list of lookalike targets, and have at it.
But what if you’re a new company and you don’t have the data you’d need to create an effective model? What if you’re small and you don’t have the resource to get all that groundwork done any time soon? What if you’re in a mature category and you’ve already completed all the set-up work – and all your competition has too? In those situations and more, innovative marketing and sales teams are starting to look at their challenges and opportunities through a different lens. Rather than viewing their ICP targets as lookalike companies who all deserve equal attention, they’re turning to sources of behavioral insight that can illuminate the actual people and real solution needs to focus on now. By shaping their own actions around the activity in the market, they’re better able to optimize resource allocations, deliver improved customer experiences and maximize their revenue.
Here’s the proof of why activity matters
When the global tele-qualification company Operatix leverages rich activity signals on behalf of their clients, they’ve achieved a 4X lift on typical conversion rates. And these meetings convert far better than average into real opportunities that progress into deals. When we executed our own extensive analysis of cold list-based demand gen tactics compared to those where we could see significant buyer activity, after over 6,000 outbound calls and more than a million emails, we showed that activity-based targeting yields an up to 7X lift in email response and a 5X improvement in MQLs qualified. What’s more, when rigorously applying the insights available to us to better prepare our callers, we’ve achieved as high as 19X improvement in meeting creation. Conversely, our cold lists required 4X more dials to get a meeting booked, and of those scheduled meetings, the show rate was 50% worse.
But not just any activity
It’s important to note that the activity we’re talking about here is materially different from three more common sources of behavioral data. First, and most common, are the “leads” you’re already buying or capturing inbound from your website and outbound with your MAP. High-volume leads are typically exhibiting a single consumption behavior in response to a single asset. And even sophisticated scoring efforts, if you’re strict, might include less than half a dozen specific behaviors. As a result, you get a lot more false positives and a lot less productive yield.
Likewise, the activity we’re talking about here is very different from the signals you can pick up about a company or an individual by scraping investment sites like Crunchbase or public relations news about big new deals or personnel changes you might get from LinkedIn. While useful as background for sales call preparation and relationship management, these are neither intense enough nor directionally powerful enough to depend on as drivers of concerted outbound activity. They can’t tell you who exactly is involved, where a buy is coming from now, or what other types of purchases could be coming in the future.
Furthermore, while there are increasingly promising sources of account-level buying signals that can narrow your total target list a great deal, without knowing the specific people involved and the issues at play at a very granular level, you simply can’t target as tightly or message as precisely as is needed to maximize productivity.
How activity matters in sales
When a salesperson has a large territory comprising many accounts, it’s typical to organize them into buckets based on some combination of ICP matching, experience and similar variables. “A” accounts will then get more attention than those ranked “B” or “C.” When buyer behavior is overlaid on such a ranking, something very interesting happens: Now the seller can make a much more informed choice of where exactly to focus their next outbound blitz for example, because they can see where there really is a deal taking shape, rather than having to continue with cold probes that commonly turn up little of immediate interest.
For field reps with only a few accounts, the value of activity is more subtle, but just as powerful. For a wide range of products, large accounts can typically have many buying centers. But if a salesperson has worked hard on a given account, maybe they’ve even sold a deal, the natural next step is to move on to another in their patch. When they have access to buyer activity data across the whole of the account, they’re able to immediately see demand present in other pockets even though they hadn’t had a chance to personally reach out to that buying center. Now they can make a truly informed choice of whether or not it’s time to move on or to strike while the iron is hot and leverage what they’ve learned into follow-on business.
How activity matters in demand gen
Because they’re often selling low-involvement products, many B2C marketers actually do have the ability to generate demand. As any first-year economics student will tell you – with all else being equal – if you lower the price of a commodity, “demand” for it can go up. B2B is different though. We may call what we do “demand gen” but it’s really about demand identification and demand capture. Unfortunately for all of us (and frankly, for our prospects) we’re all literally spending billions of dollars looking for demand where it could be at some point but actually isn’t right now. As a result, many of our processes and systems have been tailored to increase our volume of activity rather than its precision.
Activity-based demand gen turns the table on this. It puts the focus squarely on improving conversion rates through quality interaction. When teams make the switch to activity-based targeting, we see them become much more picky about what they produce and what they invest in. Rather than staying satisfied with hypothetical personas, for example, they start learning all they can about the actual people who are exhibiting buying signals. They begin to work much more closely with their inside sellers to shape cadences more intelligently. They dig into their conversational marketing tools to better address and qualify inbound traffic. And importantly, we see them move beyond output-based KPIs, to focus on opportunity creation, pipeline movement, and revenue yield.
How activity matters in ABM
As we see it, the sole purpose behind investing in ABM programs is to increase the average revenue yield and total profit obtained from a specific set of target accounts. We plan to invest more on those accounts because, by doing so, we intend to get more out of them. We’re making an educated bet that there’s more demand in there than we’ve historically been able to tap into. And to go after it, we know we’ll have to do better at marketing and sales.
A notable difference we’re seeing between practitioners who are lukewarm on ABM and those who are shouting its benefits to the rafters stems in part from the efficiency of, and the scale to which they’ve been able to grow their successes.
The very best teams are starting to move beyond only doing better with a small set of laboratory accounts to measuring success objectives using a completely new type of metric. SiriusDecisions’s “demand unit” concept provides the intellectual groundwork for the evolving approach. Rather than just looking to beat a historically derived account quota, companies are now beginning to try to calculate the real potential of the account more accurately. Then, they’re planning and investing proportionally in marketing and sales based on that potential. Activity-based targeting is making it easier to operationalize advanced approaches like this. Practitioners are using it in ABM to build programs designed to maximize share of wallet yields per account.
Activity demands action
Buyer activity signals – combining what you’re able to capture on your own properties and obtain through third party sources – provide access to a more complete view of total demand activity in a given market category. Capturing this demand requires that you make a concerted effort to go after it. If in the presence of better information, you don’t change your processes, you shouldn’t expect better yields. Furthermore, the more granular and rich the signals’ components, the greater their accuracy will be in pinpointing opportunity and the greater potential that they will offer a guide to modifying your efforts in line with real behavior in the marketplace. The logic of this seems clear: When the task is to close business, it’s essential to listen and respond to what the customer is telling you. That’s how you can deliver better on customer experience.
Marketers and sellers who are succeeding with activity-based targeting are pursuing activity aggressively. They’re throwing out rigid persona concepts to adapt to rapidly evolving buyer researcher types. They’re dynamically adjusting messaging and positioning to reflect how customers themselves view the issues. In sum, they’re becoming smarter, more agile and more customer–centric than ever before.