As you may have read in our first  of two blog posts about Progress’s journey from single-touch to multi-touch attribution , the result of the change was a large improvement in the efficiency of its marketing function, which also boosted the credibility of marketing within the C-suite. In this second post, we’ll share the 10 key lessons Progress learned during its (still ongoing) MTA journey, as told to us by Carmen Gardiner , Progress’s Director of Marketing Operations. Here they are: C-level sponsorship is a must.  “An MTA journey isn’t a small initiative for a single department to do in a month. It’s got to have C-level sponsorship throughout, and it’s got to be prioritized,” explains Gardiner. “You’ll need to have resources tied to it, with stakeholders committed across the company, from marketing to sales, IT to web to finance and beyond.” Seek early buy-in across the organization.  “Every time you think you’ve got every stakeholder in the room, you’ll discover that you don’t. Seek to get everybody on board as soon as possible, because people have to feel a part of the process for it to work,” says Gardiner. “If I could go back, I would’ve brought people on board sooner rather than later. We felt that it was a good idea to have the technology and processes down before we bought people in, but [in retrospect] I would have brought them in sooner. It took some people a long time to wrap their heads around touchpoint attribution and not campaign attribution.” Select your vendor very, very carefully.  Progress went with Bizible as their MTA vendor, but only after some pitfalls with another vendor. “Keep in mind, from the start,  what you want to have at the end of the journey because, depending on the vendor, MTA can be defined differently,” says Gardiner, “There are a lot of MTA vendors that fall into different categories, that will give you different information, different results. So think carefully about what you want at the end of the journey and then find a vendor that’s going to deliver that.” Measure and celebrate key milestones along the way.  “The MTA journey is a long road and people are going to get tired,” says Gardiner. It’s important to stop and celebrate small wins. Measuring progress is also essential. “One of our product clients wanted to see multi-touch attribution and to know about Google AdWords. We showed them multi-touch attribution and then we tied spend to each keyword, each UTM campaign. So not only could they say they spent 10 grand on AdWords and this was what they got back, but they could dig into every little AdWords campaign, and then figure out what was working and what wasn’t. They were able to refine based off that level of reporting.” Self-service works.  Ideally, you shouldn’t need to be a professional data scientist with an advanced degree to use the tools. “We made it so anybody could go to the BI [business intelligence] dashboard and take a look at it from the different facets,” says Gardiner. “They could look at it from first touch, W-shaped, full path, and get the answers they needed based on the questions they wanted answers to. Self service is really, really important. If people are just allowed to go in there and play, they’re going to be curious, ask questions, and learn.” Expect resistance, work to mitigate it.  “There was some resistance to the change,” says Gardiner. “I was told by one marketer, ‘I don’t understand this, I’m not going to use it.’ We should have brought marketing in much earlier because it’s like walking into cold water.” Yes, people might resist at the beginning, so you should expect that, but be patient and keep communicating the why and the how of the MTA change initiative. Blend the new with the old.  Progress didn’t just eliminate the old way of working and introduce the new one overnight, which would have created massive confusion and frustration among end users. INstead, it rolled out the new while staying with the old. “We would run a team’s marketing metrics meetings for six months and show their campaign data that they usually have. And then marketing ops would give them the Bizible/MTA data and we would interpret that for them,” explains Gardiner. “So they could compare and contrast the datasets, because neither of them is wrong. And after a while, our users got used to the idea that neither was wrong. Neither one is going to give you the golden bullet,” but you can gain insights from both. That “blend of old and new” approach helped prevent confusion and drive adoption. You need a mixture of touchpoints.  “Multi-touch attribution,” says Gardiner, “is just going to help you answer specific, measurable questions like, is my Google AdWords spend helping me affect the top of the funnel? It won’t answer bigger questions like ‘how did my campaign go?’ MTA helps you decide what tactics are best for each stage of the buyer journey. You need a mixture of touchpoints, not just one. Events, for instance, are great but an event might be third base [in a baseball analogy], but you have to get to first and second base before that, right?” Don’t be afraid to fail.  “You’re not saving lives, you’re learning along with everyone else. Don’t tell people that MTA is going to give them some magic path. it’s a tool they need to learn how to use well, like any other tool.” It’s also important that leadership gives space for people to fail and learn from those failures, in a process of continuous learning. MTA is a journey, not a destination.  “You’re not going to be done, ever. There’s always going to be something more that you want to know, a gap you’ll want to fill. And I’m sure the technology will continue to evolve as well,” concludes Gardiner. Achieving peak performance is a bit like chasing the sun. You may never reach it, but the journey is eminently worthwhile. Reach out to us  to learn more about how your organization can begin – or optimize – a journey towards multi-touch attribution! Update: Listen to Carmen Gardiner share 5 of these lessons – and more insights – with Sojourn’s Dan Vawter via our (now) on-demand webinar “ 5 lessons learned: How Progress improved its marketing with multi-touch attribution. “

When COVID-19 struck in March, 2020, Quest Diagnostics wasn’t completely prepared (nobody was), but its marketing team had been collaborating with Sojourn Solutions to streamline its marketing technology. As a result, Quest was able to rapidly scale up its customer engagement during a global health crisis, when demand for its testing services skyrocketed. During a recent webinar hosted by Oracle - 5 Signs You’ve Outgrown Your Marketing Automation  - Quest’s Christopher Crowe, Director of Digital Marketing, and Karin Pindle, Senior Marketing Automation Consultant at Sojourn Solutions, told the full story. The Problem: Too much complexity, too many silos Crowe began by describing the disjointed, complicated state of their marketing ops prior to its collaboration with Sojourn, which kicked off in 2018. “Back then, Quest had multiple marketing automation platforms with minimal integration with our CRM,” explained Crowe, and all this complexity created a number of problems, including: Limited internal capability and a reliance on external agencies, which was costly and inefficient; Silos were limiting Quest’s ability to gain insights from its data and manage leads -- more cross-team sharing of leads and insights was needed; A multiplicity of platforms and silos were creating confusion and a lack of efficiency for the in-house marketing teams. Best practices and lessons learned weren’t being shared effectively. Things had to change, and they reached out to Sojourn to help streamline marketing operations in order to drive more integration (of tech and teams) and more efficiency. The chosen solution: One MAP (Eloqua) Quest and Sojourn examined where the diagnostics company was, i.e., an inefficient and confusing place, and mapped out where they wanted to go in the future. Crowe sketched out what they wanted: A centralized “center of enablement” that all in-house Quest Diagnostics' marketers could draw upon for resources and support, one that would support cross-team collaboration as well as sharing of data, leads, and best practices; A reduction in the time and the cost involved for launching campaigns, including less reliance on external agencies; Clear lead flows into the appropriate CRMs, helping Sales and Marketing alignment; Increased maturity to support more campaigns and more campaign complexity. What became clear after these discussions about goals was that Quest “needed a single MAP flexible enough to offer all this functionality and also integrate with CRMs,” said Crowe.  Quest and Sojourn agreed on migrating the organization to Eloqua , largely because, as Crowe explained, “Eloqua checked all the boxes for us in addressing our needs,” providing a single, centralized source of truth and customer engagement. Crowe noted that “the Eloqua campaign canvas is so user friendly that our people could get comfortable using it quickly.” In addition, healthcare companies like Quest must comply with strict regulations around patient privacy: Eloqua has great tools for HIPAA [the patient privacy act] compliance compared to other MAPs. Implementing the solution With the goals of the collaboration clearly defined and a chosen MAP in Eloqua, Quest and Sojourn began implementing the solution. They started migrating the multiplicity of data and campaign assets contained in multiple MAPs into Eloqua. As Pindle explained, this required numerous steps, such as the consolidation and streamlining of Quest's in-house marketing processes, bringing the entire, confusing array of multi-MAP instances into Eloqua (with just a few Eloqua instances) as “a single source of truth,” cleaning the data, and improving lead management so more and better leads could be funneled to Sales. Pindle explained exactly how Sojourn approaches MAP migrations with a clear 4-step process: (1) plan and organize to identify exactly what data/assets need to be migrated and when; (2) set up, with APIs saving clients 75% on time and cost to migrate data/assets; (3) testing -- “we use humans to test everything,” Pindle explained; and (4) go live -- “we monitored Eloqua for Quest to quickly resolve any issues that might arise.” Of course, the migration and transformation process took time, but by the time the pandemic struck in 2020, Quest was in a great position to pivot and scale up its customer engagement with Eloqua.  Results: Quest Diagnostics pivots & scales B2B Marketing during a crisis Crowe explained that the 3-year collaboration with Sojourn and Oracle has made Quest a more streamlined and more productive marketing operation. The newly-implemented Eloqua MAP “helps us get the right message to the right customer at the right time,” said Crowe. ”Even though we’re running a much higher volume of campaigns and we sent 40 million emails in 2020, our campaign costs have gone down, so we’re doing more with less.” Campaigns are now easier for our people to create and develop using Eloqua, said Crowe, and they were able to ramp up customer engagement at a time when customer demand for their testing service was surging. In the end, says Crowe, ‘we’ve seen significant gains across multiple revenue measures” and “we continue to use Eloqua to create rich customer experiences.” Today Quest has greatly increased its in-house capability, relying much less on expensive agencies to fill gaps in its capabilities (gaps that no longer exist). What’s next: Driving more efficiency Chris Crowe and Quest Diagnostics, with the ongoing help of Sojourn Solutions, continue to drive benefits and cost efficiencies using Eloqua, strengthening lead generation and alignment between marketing and sales, while enhancing personalization and CX in its approach to customer engagement. Quest has effectively navigated an unprecedented pandemic and is ready to handle whatever happens next. Want to learn more about how your organization can drive more efficiency and future-proof your marketing operations, just as Quest Diagnostics did? Reach out to us here .   About Quest Diagnostics New Jersey-based  Quest Diagnostics  (QD) is a leader in healthcare testing, offering an extensive menu of testing services that include COVID-19 testing. The Fortune 500 company has some 44,000 employees around the US, and engages a wide range of customers in both the B2C and B2B spaces.

Founded in 1851, UK-based Reuters  is the world’s largest multimedia news provider, reaching billions of people worldwide each day. Reuters provides business, financial, national and international news to professionals via desktop terminals, global media organizations, industry events and directly to consumers.  Brief overview: A disjointed Demand Gen infrastructure The media company had a fractured demand generation digital infrastructure when a large part of its business was “spun out” to become Refinitiv . To plan and execute campaigns, Reuters required time-consuming, error-prone manual operations, and struggled to track campaign performance and gain full visibility into its customers’ journey.  Reuters had 10 different websites and 120 forms. Every time Reuters had an email campaign, for example, it had to build a new audience (email list) manually from scratch by pulling email addresses from disjointed systems and loading spreadsheets into Eloqua. Moreover, there wasn’t a single strategy and plan that addressed the multiple stages of the buying journey, let alone alignment with sales.  When  Juan Mejia  arrived as Director of Demand Generation in February, 2020, Reuters’ goal was the transformation of its disjointed infrastructure - integrating its digital assets, unifying its website, and connecting all customer data to its Salesforce CRM and Eloqua MAP. Ultimately, Mejia and his team completed the project in about 6 months, during a global pandemic, and in a remote work environment.  Reuters’ digital transformation strategy Because a large part of Reuters’ business was being “spun out” into an independent entity ( Refinitiv ), almost everything on the demand gen side needed to be rebuilt and reconfigured. Reuters’ infrastructure was disjointed, lacking the integration required to provide either a unified vision of the customer journey or alignment with Sales.  “We had no visibility into our customer’s journey across the funnel and we couldn't measure anything,” said Mejia. All the measures Reuters used were isolated within different channels and disconnected systems. “We’d send out a campaign and since our 10 websites with their 120 different forms and our various social media assets had isolated metrics, we couldn't connect the dots to determine how many marketing qualified leads (MQLs) we were generating or where those leads were coming from or what content might have driven them.” The strategy was to ultimately create an always-on program.  In the beginning of 2020, Reuters was restructuring their marketing team and created a new team for Demand Generation. As part of that process, they carried out an assessment with an external consulting company that allowed the new Director of Demand Generation to decide how to help shape the infrastructure.   Objectives of transformation The objective was to create and deliver an end-to-end always on digital demand generation strategy. One that drove incremental marketing impacted revenue for the business using all digital channels and stages of the customer journey. Reuters also worked on sales and marketing alignment by defining a new integrated marketing and sales funnel. This would allow the teams to better understand performance across the entire process. Ultimately, Reuters needed to transform its disjointed demand gen infrastructure into an integrated demand generation engine supported by its Eloqua MAP connected to its Salesforce CRM. The team also needed to integrate all the other systems and platforms involved, including: website, paid media, online events, interactive content and more. Reuters simply had too many manual operations for launching campaigns. The objectives included unifying Reuters’ 10 websites into one, enabling it to collect all customer data in both CRM and MAP as “a single source of truth” to enable campaign planning, execution, and reporting/attribution. Reuters also had to standardize its customer tracking and reporting, allowing it to continuously monitor and improve demand generation efforts. “We created an Always On program that aligned to the stages of the buying journey for each of our products including: email, website, social media assets, paid search - all of which were consolidated and connected to our Salesforce CRM and Eloqua MAP,” said Mejia. Working with Sojourn Solutions, the Reuters team integrated and standardized/harmonized its assets and infrastructure, gaining a unified view of its customers across channels (omnichannel visibility), as well as automating its campaigns. Reuters could measure channel effectiveness and boost ROI (for example, evaluating the efficiency of paid search).  Results Reuters built an integrated, automated demand generation engine that fuels improved campaign planning, execution, and attribution, as well as closer alignment between marketing and sales. By aligning all channels through a newly-mapped customer journey, they created an always-on program that includes paid and organic media, website, email automation, and more, delivering on a 70% growth in marketing generated revenue between 2019 and 2020 . The newly-built Reuters demand gen engine provides: Targeting . Data has given Reuters a better understanding of its customers and enabled improved targeting. “Where before we’d send campaigns of 200,000 emails, all with the same message,” explains Mejia, “now we can get more targeted by messaging micro-segments of 5,000 customers.” Alignment.  Pre-transformation, someone from Sales would make a request and marketing would merely execute the order. Marketing is now a data-powered partner that consults with Sales on strategy, tactics, and funnel optimization.  Automation. Most of the campaigns Reuters ran pre-transformation were product specific (often email blasts). Now Reuters has shifted to “always-on” nurturing campaigns based on customer behavioral data. As Mejia explains: “the always-on is essentially an ongoing, customer-informed journey where we respond to customer intent signals with relevant content.” Attribution.  Reuters can now connect demand gen investments to ROI. “Before the change,” says Mejia, “we might have been losing money for months without even knowing it.” Now Reuters can track results, as well as optimize spend and tactics on the go. Marketing has also gained more credibility and influence with senior leadership. Timescale and milestones Eloqua Design and Implementation Launch, Phase 1 & 2: Q2 & Q3 2020  Lead Scoring: Q2 2020 Integrated Sales & Marketing Funnel Design & Implementation: Q2-Q4 2020 New Multichannel Campaigns Launch: Q2 2020 New Integrated Website Launch: Q3 2020 Always On Launch: Q3 2020  Automated Data Cleansing: Q4 2020 Integrations for ON24, Splash, Hive9, Tableau: Q4 2020 SFDC Sales & Marketing Dashboards: Q1 2021 Reporting Insight, Measurement and Enhancing: ONGOING Customer summary  “We've built a demand generation machine nearly from scratch, completely changing the role of demand gen. Before, we were a tactical team that just responded to business requests and had very limited ability to demonstrate value. Today, we’re a strategic partner who creates significant value for our customers and for Reuters.” -- Juan Mejia, Demand Generation Director, Reuters To learn more about how your organization, like Reuters, can build a demand generation engine to improve revenues and marketing performance, reach out  to us today.

Data is the fuel that powers modern marketing, enabling better understanding of customer needs that leads to better engagement, better content, accurate measurement, and better marketing ROI. Data by itself is useless, however, without a mature data management infrastructure of people, processes, and technology to turn raw data into actionable insight that drives engagement and revenues. Our “Data & Insight" series focuses on building that mature data infrastructure.   Data & Insight have become more important than ever, especially given today’s rapidly changing market and customer behaviors – as well as today’s more complex digital environments – including the crumbling of third-party cookies.  The essential role and “fit” of Data & Insights into the Marketing Operations triangle of people, processes, and technology is anchored in use cases, which are prioritized based on business needs. Data & Insights are meaningless unless they support a specific, measurable, and revenue-connected goal. Yes, strategy comes into play at a higher level where you define where your organization wants to go and how you want to get there.  Your use cases inform what Data & Insights you need and how you’ll leverage them. Without use cases, you’d be operating in chaos and/or at status quo, only able to react instead of proactively driving measurable results with data and insights.  Data use cases: Driving revenues and continuous improvement The ultimate goal of leveraging data and insights is being able to predict and grow pipeline and revenue, and continuously improve your marketing effectiveness. One of the dependencies of continuous improvement is the ability to measure and benchmark exactly where you are at any given time. Another key expectation is gaining a unified view of contacts that reflects all interactions across all channels.  For many Marketing organizations, getting from here to there with their data infrastructure requires a significant investment in time and resources. It’s a heavily cross-functional approach that can require a massive paradigm shift in how Marketing organizations operate within themselves and within the larger business organization. There could be countless use cases under the umbrella of these larger, strategic goals, depending on where you are in your data maturity. Status quo as the biggest obstacle The biggest challenge to improving and maturing your data and insight capabilities is the status quo, because an organization’s desire to change must be greater than its desire to stay the same. The legacy mindsets that say, “that’s the way we’ve always done things” represent huge hurdles to overcome, especially when compounded with other challenges such as a low value associated with data in general, little to no action on insights, silo’ed functions, and beyond. Even if you somehow move past the “inertia” challenge, without a strong culture of collaboration and teamwork in place, you’ll still be faced with finger-pointing, lack of cross-functional communication and/or lack of communicating marketing’s value to the larger business organization in terms they can understand (i.e., pipeline and revenue).  4 steps to an improved data infrastructure Change is never easy and rarely linear, but you need to begin somewhere. Here’s how: 1. Business cases will be needed as the context for any defined data and insights initiative. Each business case should identify and ideally quantify the pain points and costs created by the data and insight challenges you currently face – and when I say “quantify,” I mean that the numbers must show value that’s in alignment with business impacts such as time savings, cost savings, lead creation, pipeline growth, and/or revenue impact. After you’ve brainstormed those business cases for your organization, they should be prioritized.  2. In a best-case scenario, change to the status quo would need to be driven by an executive-level Champion who brings a cross-functional mindset to driving measurable impact and who defines business case priorities, including the clearing of obstacles as needed. Since data is cross-functional in how it’s collected and leveraged, initiatives involving data must be cross-functional and have top-down support. 3. Once a business case has been presented, and received approval, a formal project plan should be built, resources assigned (having been addressed in the business case), and timelines agreed to.  4. I’d strongly suggest reaching out to us for a complimentary data review with our Sojourn team in order to help you identify opportunities to create the most value from your data and systems, and get on the right starting path to improvement. An example of Data & Insight transformation We worked with a healthcare client a few years ago that engaged us for a digital transformation project. One of the executives felt that a CDP would be the best way to solve their many challenges around data and insights.  Once we came into the project and studied their goals and resources, we realized that the organization was lacking a full integration of their core systems (MAP, CRM, ERP) causing: (1) lots of unneeded manual work such as data exports for targeting, analysis, reporting, etc. and (2) leaving many silos across the client’s functions and teams, as well as their martech and their data. Our recommendation was a plan to optimize their core systems integration, providing them with a nearly 360 degree view of their customers. In the end, we saved them an annual cost of roughly $750K in new technology, resources, and projects that the business wasn’t in a position to correctly implement and support anyway. By integrating their core systems and teams, they also developed more cross-finctional capability in how they leveraged data and insights to engage their customers and generate pipeline/revenues.  Optimizing your Data & Insight capabilities You must understand where you are now in order to get where you want to be. I’d recommend starting with some sort of Assessment (directional), Discovery (deeper directional), or Health Check (more diagnostic) in order to: (1) baseline/benchmark your current state of play regarding data and insight capabilities, and  (2) build consensus and adoption to move forward aligned to an agreed-upon maturity roadmap for data and insight. For more insight and help in improving your data quality and data management maturity, reach out  to us today.

Data is the fuel that powers modern marketing, enabling better understanding of customer needs that leads to better engagement, better content, better marketing tools/approaches, and more revenue generation. Data by itself is useless, however, without a mature data management infrastructure of people, processes, and technology to turn raw data into actionable insight that drives engagement and ROI. Our “Data and Insight Series” focuses on building that mature data infrastructure.   “Data & Insight maturity” can be defined as an ongoing journey towards improving and increasing a Marketing organization’s capabilities in leveraging data and insight. To achieve a high level of data and insight maturity, both data and insights must be fully incorporated into all decision-making and practices. Getting from where you are now to where you want to be is a process . . . Step one: Understanding where you are today  In helping our clients grow their data and insight maturity, we’ve created defined levels of maturity, with key milestones and metrics associated with each level of maturity. Our maturity model includes four levels and it helps give our customers a common baseline to understand where they’re at today based upon their assessment responses. The model also identifies what is “ideal” within each level, providing a clearly defined path for improvements, and a set of metrics to help quantify those improvements.    Improving maturity: some areas of focus More data and insight maturity means having more capability with your data, which helps you drive revenues and pipeline. Here are some specific areas where organizations typically focus their maturity efforts: Data integration. If your data is not integrated and made available to others across the organization and your systems, it’s not ready for prime time – you’ll need to plan and build key integrations to most effectively leverage your data to drive success. Data analysis and optimization. What data do you have available to fuel analysis? Is your available data accurate and relevant? Garbage in typically means garbage out. What additional data might you need to gain more accurate, fuller insights? Data Privacy and Data Compliance. Are your data practices compliant with existing and emerging data privacy requirements such as GDPR? If not, you could be facing penalties, and also end up losing the confidence/trust of your customers, who are increasingly concerned that their data privacy gets respected and protected. Approaches to growing data and insight maturity Of course, every client organization is different. Knowledge and experience count a lot when it comes to working on improving your data and insights maturity. That said, a “typical” diagnostic approach would be to start asking the right people the right questions, which would include: What’s going on now with your data and insight capabilities? What’s working and what’s not working? What’s on your “wish list?” What specific capabilities do you want to develop or improve?  What are Marketing’s priorities? What are Marketing’s use cases aligned to these priorities? What are the organization’s priorities? What are the organization’s use cases aligned to these priorities? How are you measuring success? How would you like to measure success? With these answers in hand, and after some deep analysis and follow-up, we can begin to map out what’s important, what’s not as important, what are the potential quick wins/”low-hanging fruit,” what needs to get put on the maturity roadmap, what resources are required to drive change, what timelines should be considered, and what investments are needed.  Finally, you’re able to move from planning your roadmap to achieving measurable improvements in your data and insights maturity. It’s important to begin this journey with a clear destination in mind. Your overall business strategy and goals will inform the use cases you solve for, and those use cases will inform the choices you make around technology and data, and how tech and data get deployed. Driving maturity: Pulling it all together Your stakeholders need to be working from the same playbook, meaning that your Marketing Operations people and your Marketing-at-large people are aligned around the maturity roadmap/plan and how it’s being executed, which should (of course) align with your business strategy and specific use cases. This is typically best addressed through a structured approach to change management and continuous communication, as well as by the stakeholders agreeing upon a common set of metrics and processes.  Ultimately, the goal would be to develop a cross-functional data governance model to monitor and improve your data and insight maturity.  It’s a journey, not a destination While there are key milestones along the way to data and insight maturity, based on your roadmap, the work should be considered ongoing in the same way that your customer experience and even your company performance is an ongoing, iterative process of improvement. Once you’ve reached one level or milestone, there’s always more to be done, even if that’s “just” monitoring and maintenance.  It makes good business sense to prioritize projects and actions on your maturity roadmap, always aligned with your business goals and your Marketing goals. There must be a clear and agreed-upon vision of what success looks like and clear accountability from the top down to drive the maturity process forward.  For help in improving your data quality and data management maturity, reach out  to us today.

Data is the fuel that powers modern marketing, enabling better understanding of customer needs that leads to better engagement, better content, and better marketing tools/approaches. Data by itself is useless, however, without a mature data management infrastructure of people, processes, and technology to turn raw data into actionable insight that drives engagement and ROI. Our “Data and Insight Series” focuses on building that mature data infrastructure.   The previous posts in this “data and insights” series described the importance of data in driving marketing ROI and detailed how your organization can develop a mature data infrastructure to support quality data and insights. In this post, 6 recommendations are offered that will have an immediate impact on your data quality and data maturity.  1. Improve the value of data with a data governance model.  You can achieve data governance in phases, so that it doesn't need to be super complex right from the start. A lot of organizations get stalled, and initiative dwindles, because they try to overcomplicate data governance. Three important things to focus on initially are: (1) Build a cross-functional team made up of people who have a stake in quality data. (2) Enable and empower the data team with decision-making powers, so they can identify issues and make needed changes to ensure data quality and effective data governance. (3) Map the data landscape you have, which requires having working sessions where the cross-functional team sits down together and everyone pulls up their systems and brings up the data points that are in play for them. Each team would also bring up its use cases for data and you can start discussing sources of data and their quality.  You’ll need to break data soilo’s wherever they are. So, for example, maybe marketing has their campaign data and customer segments built on certain data fields, say “country.” What happens when your ERP system changes from a three digit country code to a two digit country code, or vice versa? Your ERP is likely integrated with your CRM, so the new country code comes into your CRM. Your CRM is also integrated with your MAP. The country code change can completely blow up every single logic and country code that marketing uses in its MAP. That's a more common and chaotic scenario than you might think.  That’s why having cross-functional data governance protects the integrity and quality of your data and the systems it flows through. You need to map out your data systems, get people talking across functions and systems about any pending changes and how they might impact everyone’s use cases and data flows.  2. Perform an annual (or periodic) health check on your data and data quality, supported by a robust data health dashboard for ongoing monitoring and support.  Ideally, if you have a cross-functional data team in place, you're able to do the health check across the entire business and across all your systems. Marketing, for instance, may have data within its lead scoring program that suddenly stops getting captured for lead scoring purposes. Well, you're probably not going to notice that until a health check reveals it – during a health check, you'd actually look at the penetration of values across your key fields and you’d see that something’s gone missing. The health check helps you identify and remedy problems with your data and systems before they significantly impact everything you do. 3. Create a systems integration roadmap, allowing for “accepted levels” of integration within each phase, and communicate progress.   If your organization uses a MAP, CRM, and ERP, and your marketing team wants more customer-level data that lives within your ERP, marketing may find itself manually extracting all that data. These manual processes take so much time and effort, and can potentially diminsh the quality of the data too. So you need to know beforehand whether there's an integration in place (or not). An integration roadmap gives you that information. It tells you where you are with your core system integrations and what you have planned to expand those integrations. Knowing that can save you on needless investments, where people say, “we're not getting the data we need, so we need to invest in a CDP.” Maybe you don't need a CDP, but actually just need to better integrate what you already have – and let's put a plan in place to do that. 4. Implement controls on all data input and output sources to ensure data compliance, as well as data integrity.  When it comes to data input, people often ask, “how do we fix the data that's already in the system?” They don't necessarily think about how to fix data before it gets into the system. So looking at your form captures and your upload templates, etc., can help you ensure that you have quality controls in place before data flows in.  You could define validation rules on your forms or pull down master templates for your uploads. And it’d be exactly the same for your outputs. Make sure that not just anyone can export your data sets – you need controls in place, permissions within your user controls. That’s more important than ever because of increasing data compliance requirements. 5. Stay current on key business and/or functional team use cases to ensure data and insights are aligned.  This recommendation requires talking to people regularly in cross-functional planning meetings in order to understand and align with their use cases. Marketing operations, for instance, needs to remain aligned to the business use cases across their stakeholder teams. If that alignment is lost, then the data and insights you're capturing are going to lose value and confidence levels will erode.   6. Get a seat at the table re: martech/tech purchase decisions that will generate data within your Data Governance model.  New tech can change everything. New data could also overlap where data is already being collected. Data may need to be integrated into a BI tool or a data lake. If data comes in and is integrated with multiple systems, there has to be consideration of the impacts.  When you're looking at responsibilities around data management insight, you have to communicate with the stakeholders across functions. Planning across functions is far better than people getting surprised by unanticipated impacts that disrupt data quality and operations. For help in improving your data quality and data management maturity, reach out  to us today.

As someone who has been writing online content for the last two decades, I’ve often received lengthy “SEO (search engine optimization) briefs” listing numerous keywords to be placed into the content a specified number of times at specific places, including in the title and subheadings. “SEO requirements” have, over the years, dictated the length of content, the number of keywords within, the number of links included, the title of the content, and much more. Inorganic SEO requirements don’t help readers While content creators like myself have generally understood the importance of SEO and search rankings for online content, working with rigid SEO requirements can feel like a straightjacket that limits content creativity and doesn’t result in helpful, readable content for consumers. Almost all content creators want to make organic, creative content that truly helps people who neither know about, nor care about, SEO requirements. People simply want content that’s valuable. SEO has long sought to “figure out” what Google’s mysterious, all-important search engine algorithm requires for a high ranking. And if you think writing that sort of SEO-first content is tedious (trust me, it is), try reading this formulaic stuff – it can read like a bored robot wrote it on a bad day. Google’s update: Creating content for humans, not search engines Google created the “give the algorithm what it wants” problem and is now seeking to solve it with its recently launched Helpful Content Update . The new update began its roll out on August 25th and took until early September to conclude. The tone and content of Google’s Helpful Content Update announcement was music to the ears of every content creator and marketer who prefers to create content for real human beings rather than algorithms. “We know people don’t find content helpful if it seems like it was designed to attract clicks rather than inform readers,” said Google’s announcement. “We’re rolling out a series of improvements to Search to make it easier for people to find helpful content made by, and for, people.”  Google is well aware that search engine optimization has become more of a rigid, formulaic game than a way to create content that actually serves and informs people. Users of Google’s search engine have noticed the problem for many years and have been complaining to Google about an array of misleading tactics driven by SEO “tricks,” including misleading headlines, content filled with repetitive, distracting SEO keywords, and content that performs well for SEO but that lacks any real insight or value for readers. Bottom line? People go to Google’s search engine for information and actionable insights, not to get tricked, and Google is now advocating for its human users. “This ranking update will help make sure that unoriginal, low quality content doesn’t rank highly in Search,” says Google, “and our testing has found it will especially improve results related to online education, as well as arts and entertainment, shopping and tech-related content.” Human-Centricity: It’s been a long time coming These changes to Google’s search engine rankings that prioritize people over algorithms, that reward the helpfulness and originality of content over its adherence to some “check-the-box” approach to SEO, have been long overdue. The changes are great news for marketers and content creators who put helping people above “tricking” a search engine algorithm. The changes are also great news for people who use Google search to actually find useful, insightful, and original content. Who does the change hurt? Anyone who has been creating and posting content with the primary purpose of driving search engine visibility and traffic, rather than helping people. These SEO tricksters will now need to perform the hardest trick of all (for them): actually helping people by creating valuable content. Advice for adapting to Google's Helpful Content Update  Google helpfully provided the Search Engine Roundtable  with two sets of questions content creators and marketers can ask themselves about their content in order to determine whether it will perform well with the new content update.  Answering “yes” to some or all of the questions is a warning sign that you might be taking a “search engine-first” approach (not a “people-first” approach) and should therefore reevaluate: Is the content primarily made for search engines rather than humans? Are you producing lots of content on different topics in hopes that some of it might perform well in search results? Are you using extensive automation to produce content on many topics? Are you mainly summarizing what others have said before without adding much value? Are you writing about things simply because they seem trending and not because you’d write about them otherwise? Does your content leave readers feeling like they need to search again to get better information from other sources? Are you writing to a particular word count because you’ve heard or read that Google has a preferred word count? Google also added that “people-first content creators focus first on creating satisfying content. Answering “yes” to all or some of the questions below means you’re probably on the right track with a people-first approach to content.” Here’s the second set of questions: Do you have an existing or intended audience for your business or site that would find the content useful if they came directly to you? Does your content clearly demonstrate first-hand expertise and a depth of knowledge (for example, expertise that comes from having actually used a product or service, or visiting a place)? Does your site have a primary purpose or focus? After reading your content, will someone leave feeling they've learned enough about a topic to help achieve their goal? Will someone reading your content leave feeling like they’ve had a satisfying experience? The bottom line on Google's Search Rankings update The update from Google search offers marketers a clear message: create content that prioritizes value and usefulness for people rather than applying rigid SEO requirements. Google has, after a long time coming, finally gotten it right. Of course content should be created for people, not search engines. That’s a win-win-win for content creators, marketers, and anyone who seeks value from content.

It’s been 22 years since Harley Manning and Kerry Bodine co-wrote a seminal book about a (then) relatively-new concept called “customer experience.” The 2000 publication of Outside In: The Power of Putting Customers at the Center of Your Business  helped define and drive CX as a central concept in marketing and business. The book was based on over a decade of pioneering research conducted by Forrester’s CX research team, of which the co-authors were a part.  Manning and Bodine’s book helped define CX and what it meant for business organizations: “Customer experience is how your customers perceive their interactions with your company,” they wrote. “Once you understand that, you can manage your business from the outside in.”  Now Vice President and Research Director at Forrester, Harley Manning recently wrote a fascinating retrospective  on the Forrester blog about the lasting impact of the seminal book he co-authored. In his retrospective, he notes that many things have changed in the realm of CX since 2000, especially around digital technology and the still-developing concept of “digital-first CX,” but that many aspects of Outside In  still apply as powerfully today as they did in 2000.  Here are Manning’s five foundational truths of CX that remain ever-relevant: 1. You need your customers more than they need you. Customers can make or break your business, depending on the CX you deliver. The CX “revolution” Manning helped spark involved the idea that CX includes the product, the purchasing cycle, marketing engagement (online and offline), after-sales, and everything else that potentially impacts customers. Today, every marketer understands that multiple touch points (i.e., customer interactions) are the norm and that every single touch point is critical for building a strong CX. In his retrospective article, Manning says that too many businesses continue to treat customers as if their time and feelings don’t matter: “They barrage customers with an onslaught of spam emails, deploy customer service phone menus designed to prevent people from getting to human help, [and] goal customer service reps on ending calls quickly (as opposed to solving the customer’s problem)." That approach is anti-CX. 2. Superior CX creates superior customer loyalty. A great CX doesn’t need to be a “perfect” CX. Customers, after all, are human and understand that life can have the occasional pothole, the bad day in an otherwise good month. When brands have a clear, consistent CX strategy that gets driven across the entire organization, customers appreciate and reward the long-term CX discipline with their loyalty. When the occasional “mess ups” occur, they’re more forgiving because of the good times that have come before. CX, after all, is an ongoing, evolving relationship between brand and customer. Manning’s retrospective on the Forrester blog describes the continuing importance of CX as a way to turn “purchasers” into brand devotees. Manning defines these brand devotees as “a type of super-loyal customer who is loyal because they are having a great customer experience . . . One-hundred percent of the devotees of a brand intend to stay with it, 100% intend to buy more from it, 100% are willing to forgive it when it makes a mistake, and 100% are willing to pay a premium price for the brand (versus just 11% of non-devotee customers).” 3. Superior customer loyalty leads to superior business results. Inside Out  clearly defined the business benefits of a positive CX: businesses get “higher revenues resulting from better customer retention, greater share of wallet, and positive word of mouth, plus lower expenses due to happier customers who don’t run up your service costs.” Manning’s retrospective echoes Outside In  by reiterating the business benefits of a strong CX: “look at the business results of brands that have a high percentage of devotees. For Tesla, each devotee is worth 149% of a non-devotee. Its stock price went from $17 per share at its IPO in 2010 to over $800 per share as I’m writing this in July of 2022. That’s a return of well over 4,000%.” Simply put, maintaining and building a great CX is the best way to build any business. 4. Delivering superior CX requires business discipline. Outside In  was so impactful because it highlighted the strategic nature of CX, and how building a great CX took internal coordination, alignment, and strategic discipline around delivering on customer expectations. The seminal book made it clear that all organizational departments, as well as every single policy, process, and technology are components of a holistic CX ecosystem. CX wasn’t just the job of customer-facing departments, like sales and customer service, but involved everyone and everything in the business.  “A customer ecosystem is the complex set of relationships among a company’s employees, partners, and customers that determines the quality of all customer interactions,” the authors write in Outside In . You need a strategy to drive CX, as the book explained: “employees and partners need a shared vision: a customer experience strategy. Without that beacon, employees are forced to set out on a random walk, and their decisions and actions will inevitably be at odds with each other, despite all the best intentions.”  That need for a strategy to underpin CX hasn’t changed at all since 2000, says Manning, but has only become more challenging as CX touch points and digital channels proliferate. 5. Emotion is the key to CX differentiation. CX certainly includes filling in the potholes in the customer journey, but CX goes beyond just fixing potholes and removing friction. In order to be a superior CX, there must be an emotional component. That need for emotion hasn’t changed since Outside In  was published. As Manning writes in his retrospective: “emotion has a bigger impact on customer loyalty than either effectiveness or ease. Sometimes it has a bigger impact than both effectiveness and ease combined. That’s because effectiveness and ease are table stakes,” but emotion brings CX to a higher level. As Manning writes at the end of his retrospective, “the late, great poet laureate Maya Angelou expressed [the importance of emotion in CX] best when she said, “I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.” That’s as true for customer experience as it is for everything else in life.”

On the second day of this year’s Dreamforce  (Sept. 21, 2022), Salesforce Marketing Cloud (SFMC) announced the launch of Salesforce Genie , along with some important partnerships that will help SFMC leverage real-time data to personalize customer engagement across channels. The company announced these new partnerships during an hour-long Dreamforce session called “Deliver Customer Moments that Count.” Lidiane Jones , EVP and GM of Experiences Clouds for Salesforce, hosted the Dreamforce session by noting that “ 71% of customers  today want real-time personalization across every channel,” and brands therefore need to have the capability to (1) understand customer needs in real-time and (2) address those needs with personalized messaging across channels. That’s a difficult task because of the proliferation of systems and too much data: companies have an average of 976 separate applications  to run their business, which fragments both customer data and digital experiences.  How can marketers build the capability to personalize at scale, across channels? Jones noted that accessing and leveraging real-time data is essential for personalization efforts and orchestrating customer messaging. But getting customers to share their data is an increasing challenge. Jones noted that “90% of marketers say that recent data privacy changes have impacted their work.” Salesforce Genie: Real-time data for instant activation Jones offered a simple answer for marketers wanting to access and activate real-time customer data: the newly-launched Salesforce Genie , which Jones described as “a real-time CDP for SF Marketing Cloud that marketers can use to personalize and automate engagement through every channel.” The official SF  announcement notes that Salesforce Genie “unifies all of a company’s customer data across channels and interactions into a single, real-time customer profile, so every experience across the Customer 360/SFMC is more automated, intelligent, and real time.”  Identifying moments that matter.  Jones explained that the automatic customer profiles created by Genie dynamically adapt with incoming data and can also trigger automatic alerts to sales reps or marketers for relevant outreach. Genie “can help you identify and take advantage of the moments that matter to customers,” empowering you to “make those moments magical,” said Jones. Furthemore, Genie can help marketers with better, and more dynamic, targeting and customer segmentation, “helping you improve your ad spend” and account-based marketing (ABM) efforts. Personalization and orchestration.   Using Marketing Cloud Engagement  in tandem with Genie, marketers can take Genie’s real-time data and respond immediately to user activities by automating engagement/outreach efforts to increase conversion and cost-efficiency — for instance, marketers could automate the sending of a follow-up email immediately after an existing customer reaches a new loyalty tier, or trigger a personalized mobile/SMS and advertising journey based on an online behavior (e.g., viewing a product’s price or delivery time) that strongly signals an intent to purchase. Two new partnerships: WhatsApp and Amazon Sagemaker Jones announced a partnership with leading, global communications platform WhatsApp , enabling SFMC users to send SMS business messages via the WhatsApp platform. Matt Idema, VP of Business Messaging at Meta, which owns WhatsApp, came on stage and said that “a billion people use messaging apps every day to talk to businesses. Now, marketers can reach out with messaging on WhatsApp about promotions, support, and beyond.” Next, Jones announced an SFMC partnership with Amazon SageMaker  (a machine learning platform) that will enable marketers to integrate their SFMC data to build AI and machine learning models that can predict customer behavior and thereby inform customer engagement efforts. “With SageMaker, you can now build and train AI models with your Salesforce data,” Jones said. Of course, marketers can also build AI models with Salesforce Einstein . As the official Salesforce announcement  said, “the new integration will enable customers to use Amazon SageMaker, AWS’s machine learning (ML) modeling service, alongside Einstein, Salesforce’s artificial intelligence (AI) technology, to build new AI models tailored to the unique needs of their business — and use them in real time across the Customer 360.” SFMC in action: Build-A-Bear drives personalization Jennifer Kretchmar, Chief Digital and Marketing Officer at Build-a-Bear, spoke next about her company’s use of SFMC to drive personalization. “We use real-time customer data to personalize experiences and engage with our Build-a-Bear customers across channels,” she said.  Build-a-Bear pulls together data from various systems, including purchasing history and first-party behavioral data gained from customer website visits, to create a unified view of the customer that drives cross-channel engagement. The company has leveraged SFMC to increase digital engagement by 278%.  BaB also uses Einstein to build AI models for predictive purposes and uses real-time data to orchestrate and automate customer journeys, including using popular messaging apps for automated SMS outreach to customers. Salesforce Marketing Cloud's clear direction With the launch of its real-time data platform, Genie, and the announcement of new partnerships/integrations with WhatsApp and Amazon SageMaker, Salesforce Marketing Cloud has clearly signaled where it’s headed next: helping marketers unify their data to drive digital personalization at scale and in real-time. Contact us  for more information about how to use Salesforce Marketing Cloud and Genie to improve your marketing efforts.

This year’s jam-packed Dreamforce  included a practical, insight-filled session on Email Marketing Best Practices and Innovations , with a focus on Salesforce Marketing Cloud. The session began with Salesforce’s Heidi Robbins, Director of Marketing Strategy, describing some recent trends she’s seen in email marketing. It finished with Salesforce’s Rachel Boyles, Senior Product Marketing Manager, describing how Salesforce itself has adopted some of these recent email trends to make its own email marketing campaigns more effective. 4 pillars of effective email marketing Robbins began her talk by outlining what she called the “four pillars of effective email marketing:” Strategy Data and deliverability Design Customer Experience/CX Email marketing strategy On the strategy pillar, Robbins highlighted “the importance of setting meaningful goals and metrics” for your email campaigns. Those goals should be divided into two distinct categories: (1) internal goals around driving efficiency and (2) customer-facing goals around driving email impact. Your internal focus on efficiency, noted Robbins, should work to decrease the time it takes to build emails. Starting each email from scratch, she said, is wasteful and limits customer impact. Automating your processes around how you build and send emails is, Robbins explained, a key component of streamlining your email workflow to make it more efficient and scalable.  When it comes to impact on customers, the second strategic focus, Robbins asked marketers to “look beyond the open rate, which is a superficial metric, and instead connect your metrics back to the business.” Repeating a phrase that was the focus for much of Dreamforce 2022, Robbins also told marketers to “focus on making moments that matter” by seeking to connect on a deeper, more emotional level with customers. Data and deliverability key in email marketing Robbins explained that driving customer engagement is the key for email deliverability. “Engagement gets you better data and improves your brand reputation, both of which positively impact deliverability.” Robbins asked marketers to “build a data framework that includes the data you have now, the data you need, and the data you want.” Quality data enables personalization, which in turn enables better engagement and better email deliverability, creating a virtuous cycle. Email marketing and design Robbins noted that effective email campaigns should have a standard look and tone that recipients can feel. She therefore asked B2B marketers to... ...“develop an email Design System, which is a collection of reusable components, guided by clear standards, that can be quickly assembled to create digital experiences.” Customer Experience/CX in email marketing “The biggest CX trend in email marketing is to make things fun and to put play at the center of the email experience,” said Robbins. Doing that well takes authenticity and a commitment to building community, both digitally and in real life (an approach Robbins calls “IRL + URL”). How Salesforce approaches its email marketing Rachel Boyles took the microphone next and began describing how Salesforce approached email campaigns for its own B2B customers. She began by detailing six big challenges Salesforce shares with every other B2B brand using email marketing: Having siloed and unused customer data; Facing the need for ongoing product education of its customer base; Competing priorities for the marketing team and limited time/resources; Noise coming from the brand and to customers across multiple channels and internal teams; Lack of customer personalization across content assets; Marketing team members with varied skill levels and experience with email. Boyles tackled these challenges with three strategic goals in mind: To provide personalization at scale; To automate behavior-based customer journeys; and To deliver connected, engaging customer experiences. “We started by building our marketing journey around our B2B customer’s journey,” said Boyles, using Salesforce CRM and data to segment customers through multiple factors such as region, industry, and title. “We then aligned our content delivery around customer behaviors, especially connected to their buying stages and their online behaviors,” she said. For example, if a prospect downloaded a white paper promoted in an email, a Salesforce rep would automatically be alerted and a follow-up recommendation would be generated for the rep. Finally, Salesforce focused on content quality: “we created messaging that stood out, with clear calls-to-action, less jargon, and more concise language.” Nobody has any time for emails that aren’t immediately, clearly relevant to them. Salesforce “activated our CRM data for personalizing email messaging, and worked continuously to ensure that our customer data was reliable, timely, and accurate,” Boyles said.  Regarding Robbins’ earlier recommendation that marketers create a Design Center of reusable, modular assets available for building email campaigns, Boyles explained that Salesforce has done exactly that. “We created a modular design center so our marketers could easily drag and drop assets” into an email, giving emails a standard look and feel for specific campaigns. “We also leveraged collaborative design tools so more of our people could provide input and ideas on design choices,” she said. Both Robbins and Boyles concluded the Dreamforce session by explaining how marketers could learn more about the various Salesforce Marketing Cloud tools to help them improve email marketing effectiveness.  Are YOU interested in learning more about how to help your teams build better email campaigns with Salesforce Marketing Cloud? We can help - contact us  today.

The proposed American Data Privacy and Protection Act (ADDPA) , now pending in the House of Representatives, would provide a wide-reaching national privacy standard, overriding existing state privacy laws. If the ADDPA becomes law, marketers would only have to conform to one, national data privacy regulation instead of the patchwork of state laws currently covering the same ground - including laws in California, Colorado, Connecticut, Utah, and Virginia (a dozen other states are now considering data privacy laws as well). The ADDPA would likely serve to loosen some of the highly pro-consumer privacy regulations now in effect under the California Data Privacy Law. For this reason, the ADDPA could face opposition in the Congress from California legislators. As a Los Angeles Times story  recently explained, [U.S. Speaker of the House and California Representative Nancy] “Pelosi’s public opposition, which echoes concerns from [CA] Gov. Gavin Newsom and the California Privacy Protection Agency, marks an escalation in the standoff between California lawmakers and a large bipartisan group of [ADDPA] supporters.” What the ADDPA looks like While the proposed federal privacy law is still subject to change during the legislative process (it’s become clear that California wants to keep its more pro-consumer data privacy law), the broad outlines of the current federal proposal include the following, according to a report  from the Congressional Research Service: Data collection and management The ADDPA would cover information that “identifies or is linked or reasonably linkable” to an individual. The bill would prohibit covered entities (including B2B marketers, of course) from collecting, using, or transferring covered data beyond what is reasonably necessary and proportionate to provide a service requested by the individual, with some exceptions. It also would create special protections for certain types of sensitive covered data (like health-related data). The ADDPA would also require covered entities to adopt data security practices and procedures that are “reasonable in light of the entity’s size and activities.” The Federal Trade Commission  (FTC) would be authorized to issue regulations specifying these data security requirements.  Analysis of impact:  Most of the ADDPA’s provisions around data collection and data management are already imposed on marketers via GDPR and the California Data Privacy Law, so not much would here. Again, the federal law is generally less protective of consumer privacy than the California law, which is why some of the Big Tech companies support it. Consumer control and consent ADDPA would give consumers various rights over covered data, including the right to access, correct, and delete their data held by a particular covered entity. It would further require covered entities to give consumers an opportunity to object before the entity transfers their data to a third party or targets advertising toward them.  Analysis of impact:  On these “consumer control and consent” provisions, the ADDPA is aligned with GDPR, so it would very impose minimal “new requirements” on B2B marketers. Obviously, consumer consent and consumer trust are intertwined – B2B marketers should be asking customers for consent as a standard procedure anyway, in order to build trust and foster more data sharing. Third-Party data collecting entities ADDPA would create specific obligations for third-party collecting entities, whose main source of revenue comes from processing or transferring data that they don’t  directly collect from consumers (e.g., data brokers). These entities would have to comply with FTC auditing regulations and, if they collect data above the threshold amount of individuals or devices, and would have to register with the FTC.  Analysis of impact:  The ADDPA shows a clear intent to regulate data brokers through the FTC, which will have the power to audit and issue regulations on how data brokers collect and use/sell data. This is clearly bad news for third-party data, which has become problematic anyway due to changes in third-party cookies (in short, they are getting eliminated). Protections for youth The ADDPA would create data protections for individuals under age 17, including a prohibition on targeted advertising, and would also createe a Youth Privacy and Marketing Division at the FTC. These additional protections would only apply when the covered entity knows the individual is under age 17, though certain social media companies or large data holders would be deemed to “know” an individual’s age in some circumstances.   Analysis of impact:  Here, the ADDPA is responding to a number of recent studies  making the connection between online activities and negative psychological impacts on young people. These additional protections give the FTC the power to crack down on excessive ad targeting and other forms of engagement to young people. Civil Rights and algorithms The ADDPA would prohibit most covered entities from using covered data in a way that discriminates on the basis of protected characteristics (e.g., race or sex). It would also require large data holders to conduct algorithm impact assessments, and submit these assessments to the FTC and also make them available to Congress on request. These assessments would need to describe the entity’s steps to mitigate potential harms/discrimination resulting from its algorithms, among other requirements.   Analysis of impact:  There’s been a growing public concern that algorithms have massive impacts, but are also beset by patterns of discrimination. Under the category of “garbage in, garbage out,” regulators don’t want data that merely reflects patterns of historical discrimination to be fed into algorithms. Under the more pro-consumer California law, consumers can opt-out of having their data used to build algorithms, while the ADDPA does not allow this, it does empower the FTC to regulate algorithms. Private right of action The ADDPA would create a private right of action starting two years after the law’s enactment. Injured individuals, or classes of individuals, would be able to sue covered entities in federal court for damages, injunctions, litigation costs, and attorneys’ fees. Individuals would have to notify the FTC or their state attorney general before bringing suit. Before bringing a suit against a small- or medium-size business, individuals would be required to give the violator an opportunity to address the violation.  Analysis of impact:  This “private enforcement” provision of the ADDPA is very similar to enforcement mechanisms within GDPR and the California law, so not much would change here for B2B marketers. Bottom line? The ADDPA, even if it becomes law, will likely not create additional requirements when it comes to how you collect and manage customer data, largely because the proposed federal law is less protective of data privacy than the current California data privacy law. Want help in how you collect and manage your data so you not only comply with data privacy regulations but also optimize your marketing ROI? Contact us  to start a conversation.

This year’s Tableau session at Dreamforce, called “Use Data to Boost Your Bottom Line,” focused on how the Salesforce BI (business intelligence) tool enables companies to: (1) bring all their data into Tableau, (2) customize their Tableau dashboards, and (3) generate insights and transform them into better decisions. While Tableau is typically described as a business intelligence dashboard, it might better be viewed as an organization’s bridge connecting its raw, unfiltered data on one side with insights and actions on the other. The function of Tableau is to be the platform where data gets transformed into insights that are easy to view and analyze, forming the foundation for organizational decision-making. Salesforce’s Greg Bennett, Director of Product Marketing, and Salesforce’s Darin Bergeson, Senior Manager, Product Management, led a Dreamforce 2022 session on Tableau that was rich in detail and, yes, filled with insights. More data means a bigger “data gap” Bennett described how the pandemic has accelerated digital transformation in multiple areas of human endeavor, from how work happens (remote and hybrid work models now predominate) to how people shop, seek entertainment, access healthcare, and do nearly everything else. “Every digital transformation is at heart a data transformation,” said Bennett, “More data is being produced today than ever before, and is available to drive insight and action.” But a “data gap” remains, explained Bennett, a wide chasm between expectations for data and how data is actually being leveraged (again, with Tableau serving as the bridge over that data gap). Bennett cited an IDG survey which found that 83% of CEOs want their organizations to be more data driven, while only 30% of employees believe their organization is actually data driven. That’s a huge gap of 53% between expectations for data and “data reality.” 4 factors driving today’s data gap Bennett detailed 4 factors he believes are “driving today’s data gap”: 1. Data chaos, which is the result of “so many sources of data that create a huge volume of data” that organizations simply don’t have the present capacity to leverage into insight. More data is not a solution – rather, more data can lead to more needless complexity and more confusion.  2. Lack of data skills. The people who have access to data don’t necessarily have the skill set to transform raw data into data analysis and data-informed action. In the past, data scientists did much of this manually-intensive and highly-specialized work, but Bennett believes we need to make these data capabilities available to everyone, something Tablea does with a variety of AI and automation capabilities. 3. Lack of data culture. Bennett believes that “organizations should be putting data at the heart of its conversations and decisions. That isn’t happening enough today because data often remains an untapped resource.” Too many people continue to make decisions based on hunches and past experience, which can lead to bad decisions in a world that’s changing so rapidly. 4. Lack of enabling tools. The first three factors leading to the “data gap” can only be improved by giving people the tools to facilitate turning data into insights and actions. As Bennett explains it, “Tableau can help organizations optimize their existing processes with data, lower the current barriers to insights, and get data working harder and smarter for you.” Accelerating insights and actions with Tableau  Bennett notes that Tableau is a flexible tool, customizable by department – finance, HR, sales, marketing, and beyond – as well as by industry. With Tableau, he says, “we’ve created pre-built and flexible dashboards for every business function and every industry. For example, we help the sales function predict sales and revenue, which also helps with production planning and finance.” Bergeson then did a demo of some of Tableau’s pre-built dashboards. A marketer, for example, could simply pull down a “function menu” and select marketing from many other functions (finance, HR, etc.). Tableau, which is seamlessly integrated with Salesforce CRM data as well as data from many other sources, would then integrate and analyze available data in order to populate a pre-defined dashboard display for the marketing (or other) function. Of course, the marketer could then customize the pre-defined dashboard to better meet their specific needs.  Bennett then offered an example to illustrate the point. Software firm “Red Hat integrated more than 60 sources of data into Tableau,” he said, which not only scaled analytics across their organizations and helped create a data culture, but also saved them significant time on reporting and data sharing,” across the company. Bennett added that Tableau allows users to do deeper dives into data points displayed on the dashboard, for example by examining the source of the data used to generate insights, as well as how that data was collected – something Tableau calls “data lineage.” The Tableau session takeaways Bennett’s exploration of today’s “data gap” and its drivers was both compelling and true for most organizations that are simply awash in too much data. He gets high grades for diagnosing a common and mission-critical organizational concern – the lack of organizational capacity to leverage data into insight and better decisions. Tableau is clearly committed to closing the data gap through integrating an organization’s data and populating it into a business intelligence dashboard with best-in-class analytic capabilities fueled by automation and AI (Einstein, in the case of Salesforce). Will Tableau work well to bridge the data gap at your organization? Probably yes, but that’s a hard question that requires an understanding of your current data infrastructure and your strategic goals for the use of data. Want to learn more about Salesforce Tableau and how it might help you turn data into better decision-making? Contact us  for help.