“Salesforce announces Marketing Cloud Growth…” WAIT 🤚, it’s not what you think! (and it’s not necessarily a bad thing )
Let’s get one thing straight: despite Salesforce’s tendency to name all products in the marketing area with the same root “Marketing Cloud” we’re actually talking about a new product here, which at most shares intentions with its dad (or mother, whatever…) Marketing Cloud.
A new product designed for SME (Small-Medium Enterprises) marketing, entirely developed on the Salesforce platform (Einstein 1 to be precise) and strongly interconnected with Einstein’s AI and Data Cloud functionalities.
In a nutshell 🥥? Creation of simple marketing campaigns delivered directly from the platform, leveraging:
segment generation through Data Cloud + AI
content creation (Email, SMS, or landing pages) with generative AI
journey creation through Flow
KPI analysis through dashboards
Why might it be interesting?
It seems like a straightforward tool, which could be a plus point in Italian scenarios where the classic Marketing Cloud is often oversized.
From what we see, it’s truly “Einstein first“: generative AI isn’t an option, but the primary mode of interaction for content generation.
Its integration into the platform + the presence of AI will make it very appealing to customers, particularly in the spotlight from a Salesforce perspective.
PAY ATTENTION: Salesforce already has a marketing product developed on its platform, the famous Pardot, now Marketing Cloud Account Engagement, which, just to confuse matters, has an edition called Growth (sigh). Although both seem to be positioned for B2B, this new one seems much more “customer-oriented” and potentially multichannel.
This guest blog is delivered by Leah Fainchtein Buenavida, a technology writer with 15 years of experience, covering areas ranging from fintech and digital marketing to cybersecurity and coding practices.
The demand for constant, personalized, seamless customer experiences is always growing. According to the Connected Customer report, 67% of customers say their expectations for good experiences are higher than ever.
Marketers understand the value of personalization. However, delivering personalization at scale remains a challenge for many brands. Tools like SalesForce Marketing Cloud can help you automate personalization, make data-driven decisions, and create dynamic content.
This post reviews some of the platforms included in the Marketing Cloud platform, with a focus on the Personalization Builder.
What is Salesforce Marketing Cloud?
SalesForce Marketing Cloud is a marketing platform that provides multiple tools for managing the interaction between a brand and its existing or potential customers. The platform enables you to contact customers on the right channel, at the right time via email, SMS, or social ads, create multi channel experiences, and increase sales and customer acquisition.
This model of Marketing Cloud is based on the ME2B approach, where customers are defining the kind of relationship they want with brands. Brands need to create experiences that promote trust and strong connections with their customers. Marketing Cloud tools enable them to establish this relationship and collect important information about their users, their preferences, and opinions.
What Can You Do With Marketing Cloud?
The Salesforce Marketing Cloud consists of seven primary products that leverage Artificial Intelligence (AI) technology and predictive analytics to connect you with your customers. You can interact with customers through mobile messaging, email, digital advertising, social media, and website content. Primary products include Email Studio, Mobile Studio, Social Studio, Advertising studio, Einstein, Journey Builder, Personalization Builder.
AI-based marketing tools can turn standard content into hyper-personalized messaging. Personalized emails, for example, have a greater chance of being opened and engaged with than their traditional alternatives. Only the most relevant communication can generate a positive response from your audience. Marketing Cloud helps you place the right content into your web messaging and email along the customer journey. Machine learning capabilities enable you to continuously improve and adapt the customer journey, keeping content relevant and engaging.
Salesforce Einstein
Einstein integrates Artificial Intelligence (AI) technology with Salesforce’s Customer Relationship Management (CRM) system. Einstein uses predictive analytics, machine learning, and Natural Language Processing (NLP) capabilities to analyze customer data. Einstein’s AI algorithms leverage this analysis to improve its capabilities, and perform more accurate analysis. This technology can analyze user data in different sectors:
Sales—helps to increase conversion rate by predicting the probability of a customer to purchase a product.
Customer service—helps with predicting issues, classifying and routing of cases. Also includes intelligent chatbots to help customers resolve common problems.
Marketing—it helps to increase conversion rates by predicting who is more or less likely to engage with an email by engagement scoring and predictive recommendations.
Retail—uses customer data to identify the products a visitor might want, both in digital and traditional commerce. Brands can increase revenue by predicting if a consumer is more or less likely to purchase a specific item.
Salesforce Personalization Builder
The Salesforce Personalization Builder is based on Einstein. It uses predictive analytics to deliver personalized content to customers based on their preferences. The Personalization Builder shows you the behavioural history, real-time interactions, and buying preferences of customers. You can use this data to predict how they will act in the future, and understand the motives behind their actions. These insights can help you improve your customer engagement strategy across all relevant channels.
You can use Salesforce Personalization Builder together with other Marketing Cloud platforms to further improve your marketing campaigns. Content Builder for instance, manages all content and assets in one location. You can use Analytics Builder to track the performance of content campaigns, measure their success and use Personalization Builder to extract valuable insights from the data to adjust a campaign accordingly.
How to Set Up the Personalization Builder in Marketing Cloud
The process below describes several technical steps that can help you set up the Personalization Builder in Marketing Cloud.
Step 1—content or product
Decide if you want to use content or product or both, and set up your catalog with field attributes, and activity tracking for category view, purchases, shopping cart. A catalog stores all your content or product data with as many details as possible. This includes price, URL’s, stock, description, keywords, and categories.
Step 2—import your catalog
The catalog importing task in Personalization Builder is time consuming. There are two possible options:
Flat-file upload—the uploaded file is added to a publicly available web URL or an FTP account and imported into the Builder twice a day.
Streaming updates—updates and adds content and products through another snippet of JavaScript.
You have the option to map your catalog fields with the default fields of Marketing Cloud, and select which fields to tag. Tagging determines the fields that are used to build your affinity per profile. For example, tag the fields for category and brand, where brand is Toshiba and category is TV.
Step 3—data collection
Once the catalog is in place, you can start collecting user data. You might need help from your developer to implement all the necessary Collect Codes for behaviour tracking. These Collect Tracking Codes are JavaScript snippets that are used to gather data about known contacts and unknown visitor behaviour.
First, collect the available JavaScript snippets of Marketing Cloud. Start with the Base Collect Code that needs to be implemented on every page of your web site. Find the code in the official documentation.
Next, you need to capture user attributes and information. This script identifies your unknown visitors:
Turn on the data extensions of Einstein. Follow the next steps to enable the Personalization Builder populate these data extensions in Contact Builder.
Navigate to the Personalization Builder Status tab.
Reveal the drop-down menu by choosing the grey Settings cog
Click on Data Extension Settings
Click on Enable Einstein Data Extensions
Click Save.
Conclusion
The most common challenge that brands encounter when using SalesForce Marketing Cloud is not knowing how to use its different tools. Marketers need to know which tools to use at the right time, and for what purpose. Salesforce Personalization Builder helps you better understand how your customers behave and why. It enables you to see your customers’ behavioural history, real-time interactions, and buying preferences. You can set it up with only a few technical steps.
This post is delivered by Alex Rogora, an Analyst and Cloud Administrator specialized on Marketing Cloud. Thanks to this multipurpose profile – a computer science background, university degree on Communication and several years of work experience in mail marketing – he is member of the Solution team for WebResults (Engineering Group), that studies new technologies released by Saleforce.
The life of a Marketing Cloud consultant can be hard, especially when it comes to migrating configurations from one Business Unit to another.
Of course, some assets or Data Extensions can be
shared between multiple BUs in the same environment, but if we talk for example
about customer journeys, automations, or data model, the only solution was to replicate
the configuration manually without any type of support.
This was true until few months ago, when the Deployment Manager made its quietly debut on the AppExchange.
As reported in the dedicated page, Deployment Manager is a Salesforce Labs app that “allows users to import/export Marketing Cloud campaign configuration”.
Easy, clear and even free: let the revolution begin!
WHAT CONFIGURATIONS ARE WE TALKING ABOUT?
The first features enabled in April 2019 were the canvas structure of customer journeys and in a short time the export of Data Extension schemas were added as well.
To be honest, not every element that make up the journey is replicated at the moment: for example the entry source is missing and for some activities there is only the placeholder, but it’s a good place to start.
For Data Extensions, the snapshot is limited to the
fields, while the contained records are not exported. But in my humble opinion
I think this is right, because we have privacy constraints and often the data
in a test BU is different from that used in production.
A few months later the Deployment Manager added a partial support for deploy automation and, in certain cases, also for the related activities contained.
For example, if the automation contains a query activity, the extracted JSON file will also contain the information to generate the activity itself and the corresponding destination DE. While, unfortunately, in the case of “send emails”, neither the related activity nor the associated creativity will be created, but we’ll only see the placeholder in the automation step. Fortunately, the import report is quite descriptive and allows you to obtain useful information on the individual elements copied.
Finally, the Deployment Manager supports the
possibility to export attribute groups of the data model.
In this case the deployment process seems to be quite
complete, because both the attribute sets and the necessary DE are
automatically exported.
But this is only the beginning clearly.
With a look to the near future, hypothesis predict about content builder folder organization, asset and the completion of existing journey features.
HOW DOES IT WORK?
Well, it’s very simple.
Once installed through AppExchange in both BUs, the source and the destination one, Deployment Manager allows you to export the configurations you want to copy by creating a JSON file that can be easily downloaded.
This snapshot contains the metadata of the journey, DE, attribute group, or automation without any customer data or campaign data. The exported file can therefore be easily re-imported into the target business unit, even in different accounts.
Wait, wait..wait!
Did you just say also in different accounts? Yes, even
in BU belonging to different marketing cloud enterprises.
And want to know
another amazing thing?
We can export / import multiple configurations at the same time, in the same snapshot, with few clicks!
So, even though there is still a bit of
stuff to fix / add, it’s clear that this app allows all customers to decrease
the effort needed for production deployment processes, while also minimizing
the risk of error during this phase.
Deployment Manager
is also a useful ally for Salesforce partners, because it allows you to easily
recreate configurations previously implemented in other environments in the
customer’s account and you
can also store a snapshot for templating, backup, auditing, or version control.
And the audience quickly noticed it.
Deployment Manager was
one of the highest rated sessions in the Partner Lodge at Dreamforce 2019 and it’s
also the 2nd most downloaded Salesforce app which allows partners to
streamline account creation, migration and setup.
Believe me, we will hear more about it in the next months!
This post is brought to you by Luca Miglioli, an Information System Analyst that works at WebResults (Engineering group) in the Solution Team, an highly innovative team devoted to Salesforce products evangelization.
Some months ago, Google announced a secure-by-default model for cookies, enabled by a new cookie classification system. Changes concern in particular to the SameSite attribute: on a cookie, this attribute controls its cross-domain site behavior, that is if no SameSite attribute is specified, the Chrome 80 release sets cookies as SameSite=Lax by default while previous to the Chrome 80 release (the current one), the default is SameSite=None. Ok, but what does it mean?
To safeguard more websites and their users, the new secure-by-default model assumes all cookies should be protected from external access unless otherwise specified: this is important in a cross-site scenario, where websites typically integrate external services for advertising, content recommendations, third party widgets, social embeds, etc. and external services may store cookies in your browser and subsequently access those file.
These changes are being made in Chrome, but it’s likely other browsers will follow soon: Mozilla and Microsoft have also indicated intent to implement these kind of changes in Firefox and Edge, on their own timelines. While the Chrome changes are still a few months away, it’s important that developers who manage cookies assess their readiness as soon as possible: that’s why Salesforce rapidly notifies its customers and partners with an annoucement (contained in the latest release notes, Spring ’20). Especially, the announcement explains that:
“Cookies don’t work for non-secure (HTTP) browser access. Use HTTPS instead.”
Check the URL of your website, if it starts with http:// and not https:// then you’ll need to get some form of SSL certificate. It’s probably worthwhile checking all of the links to your pages to make sure they are directing the the https:// version of the page. For example, make sure you are using the HTTPS links if you are embedding Pardot forms on your websites: this was not enabled for our organisation by default, so it’s likely that your organisation may need to do this.
“Some custom integrations that rely on cookies no longer work in Google Chrome. This change particularly affects but is not limited to custom single sign-on, and integrations using iframes.”
1st, 2nd and 3rd party integrations might be seariously impacted. Salesforce recommends to test any custom Salesforce integrations that rely on cookies owned and set by your integration. For example, an application not working as expected could be Marketing Cloud’s Journey Builder not rendering in the browser or Cloud Pages/Landing Pages/Microsites returning blank pages. If you determine that your account is affected by the SameSite cookie change, you need to investigate your implementation code to ensure cookies are being utilized appropriately.
Ok, this looks a little bit scary, but don’t worry!
First, developers and admins can already test the new Chrome’s cookie behavior on the sites or cookies they manage, simply going to chrome://flags in Chrome (type that in the URL bar) and enable the “SameSite by default cookies” and “Cookies without SameSite must be secure” experiments.
Second, developers can still opt in to the status quo of unrestricted use by explicitly setting SameSite=None; Secure: only cookies with the SameSite=None; Secure setting will be available for external access, provided they are being accessed from secure connections.
Third, If you manage cookies that are only accessed in a same-site context
(same-site cookies) there is no required action on your part; Chrome will
automatically prevent those cookies from being accessed by external entities,
even if the SameSite attribute is missing or no value is set.
That’s all! You can still find more detailed
info here: