A customer data platform (CDP) is a customer data unifying software. You can manage your customer experience across every touchpoint by adding it to your MarTech stack. This software brings together data from all sources – batch, streaming, structured or unstructured, transactional or demographic – and makes it available 24×7 to all enterprise users.Today, CDPs have become a “must-have” tool for marketers as it helps collect customer data from all sources to create a 360 degree profile of every client. The idea is to deliver the “ultimate customer experience”. In order to do that, certain best practices have to be put in place vis-à-vis the use of the CDP, and this article looks at some of the important ones.<h2 class="ql-align-center">Top 10 CDP Best Practices to Adopt</h2>What are the 10 CDP Best Practices to Enhance Customer Experiences? Let’s first give a glance at the ten best practices for using a CDP itself for better customer experience:<ol><li>Identify the key business objectives for using a <a href="https://www.expressanalytics.com/blog/how-to-get-insights-from-customer-data-platform-cdp" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">CDP</a></li><li>It’s important to have clear goals for implementing a CDP, such as increasing sales or reducing costs.</li><li>Establish a comprehensive data governance framework</li><li>A comprehensive data governance framework will ensure that all data is handled responsibly and that data accuracy and completeness is maintained.</li><li>Select the right CDP technology</li><li>There are a number of different CDP technologies available, so it’s essential to choose one that meets the specific needs of your business.</li><li>Train employees on how to use the CDP</li><li>Employees need to be trained on how to use the CDP and how to manage and protect data.</li><li>Implement a data retention policy</li><li>It’s essential to determine how long business data will be retained in a CDP and to have a data retention policy in place.</li><li>Use data analysis tools to improve business operations</li><li>Data analysis tools can help businesses improve their operations by identifying patterns and trends in data.</li><li>Use CDPs to engage with customers on a more personal level</li><li>Plan plain and clean data feeds</li><li>Optimize for Real-time result</li><li>Measure the Success of your CDP Implementation</li></ol>-----------------------------How does a CDP help Marketers Strengthen Customer Relationships? <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">&gt;&gt;&gt; Schedule a call &gt;&gt;&gt;&gt; </a>-----------------------------<h2 class="ql-align-center">Mistakes to Avoid when Implementing A CDP</h2>There are some common mistakes that companies make while deploying a CDP.<ol><li>One is failing to integrate CDP data with other data sources, such as marketing automation platforms and CRMs. This can lead to data silos and make it difficult to get a holistic view of the customer.</li><li>Another mistake is not having a clear plan for how the CDP will be used. Without a clear use case, it can be difficult to justify the investment in a CDP.</li><li>Finally, some companies make the mistake of trying to do too much with their CDP, instead of focusing on a few key use cases. By doing this, they risk overwhelming their teams and not getting the most out of their CDP.</li></ol>With that out of the way, let’s move on to this post’s main topic – how to better use a CDP to enhance your customer’s experience. A CDP can be used to personalize the customer experience and to provide additional services.<h2 class="ql-align-center">How You can Use a CDP to Enhance Customer Experiences?</h2>Now that we’ve seen what a CDP is, and some of the best practices for using it, let’s take a look at how you can use a CDP best practices to enhance customer experiences.<ol><li>Use a CDP to enhance customer experiences across all touchpoints: One of the key benefits of using a CDP is the ability to improve customer experiences across all touchpoints.</li><li>Collect customer data from all sources: It’s important to collect <a href="https://www.expressanalytics.com/blog/customer-journey-map" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">customer data</a> from all sources in order to create a 360 degree profile of every client.</li><li>Use data analysis tools to identify patterns and trends in data: Data analysis tools can help businesses improve their operations by identifying patterns and trends in data.</li><li>Use CDPs to personalize the customer experience.</li><li>A CDP can be used to personalize the customer experience and to provide additional services.</li><li>Focus primarily on top revenue generating clients (if financial resources are limited): If financial resources are limited, it’s critical to focus primarily on top revenue generating clients.</li><li>Use CDPs to improve customer experience across all touchpoints: It’s important to use a CDP to improve customer experiences across all touchpoints in order to create a truly omnichannel customer experience.</li></ol>To begin with, the first step would be to lay down a roadmap for enhancing the customer experience. <h2 class="ql-align-center">Laying Out A Roadmap</h2>Your business’ overall target are tied in directly with your marketing goals, which, in turn, are directly or indirectly tied in to your customer experience. For all of this, you need to work to a plan, which has to be put down on paper. This has to be shared with all stakeholders involved in the decision-making.The roadmap must ask basic questions like: What do customers want from your business? How do you meet those needs? The plan must not only have questions, but answers, too.There should be measurable key performance indicators (KPIs), which may include customer satisfaction (CSAT) scores and net promoter scores (NPS).Whenever you make a commercial or marketing decision, you can use your CDP best practices roadmap as a compass – whether you’re customizing your CDP capabilities or identifying which data sources you’ll need.<h2 class="ql-align-center">Ensuring Your Business Goals Sync with Customer Experience Plan</h2><a href="https://www.expressanalytics.com/services/marketing-analytics" rel="noopener noreferrer" target="_blank" style="background-color: transparent;">Customer experience </a>could become the driving force in your enterprise, taking it towards its commercial goals. You will, however, need to ensure that your business goals and customer experience are in alignment. It’s the only way that you can make sure that you reach the target market and meet their needs in a way that improves your profits.There are a few ways that you can do this. You need to make sure that you understand your customer’s needs. What motivates them? What makes them happy? Do you have a strategy that actually anticipates a customer’s needs even before they are expressed? Once you know these things, you can start to tailor your products and services to meet those needs.<h2 class="ql-align-center">Optimizing Marketing Campaigns With A CDP</h2>By combining various customer data points, such as email addresses, phone numbers, first-party cookies and purchase data, the platform creates a single customer profile. In fact, once your business acquires a CDP, the aim should be to unify all disparate sources of data. Once done, you need to send out personalized content to consumers.CDPs give marketers complete control over customer related data collection and its segmentation. They offer integration of data both identifiable and anonymous customer data with any external source such as a CRM, point of sale (POS) machine, smart computing device, website and so on.A CDP takes the confusion out of your marketing campaigns. Data management has become increasingly complex in recent years, with the rise of big data and the proliferation of devices and sensors. This has made it difficult for marketers to keep track of customer data and use it effectively. A CDP helps marketers overcome these challenges by collecting, organizing, and analyzing customer data from multiple sources.But how does one know which content to send out? This is where the use of customer data points come into play. By understanding what actions consumers actions took on your site or app, you can better predict what they will want to see next.For instance, if a consumer makes a purchase on your ecommerce site, you can email them thanking them for their purchase and suggesting similar items that they might be interested in. Customers are extremely valuable to businesses, and with the help of a CDP best practices, you can optimize your marketing campaigns in order to create a more engaged customer base.-----------------------------How do You Choose a Customer Data Platform? <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">&gt;&gt;&gt; Schedule a call &gt;&gt;&gt;&gt; </a>-----------------------------<h2 class="ql-align-center">Using The CDP As An Enabler</h2>That’s right. Your CDP is the sole central source of truth. Gone are the days when simply tracking a customer’s journey would suffice. Today, it’s all customer experience with a brand. A customer or prospect uses multiple channels and multiple devices to shop.They expect their shopping journey to be seamless, and get frustrated when it is not. That’s where a CDP plays a big role. This critical piece of software helps not only properly collect data but also activate it for personalization, thus driving sales.<h2 class="ql-align-center">How Can You Ensure Successful Adoption Of A CDP?</h2>Before signing off, here are a few CDP best practices to keep in mind when implementing a CDP.<ol><li>It’s important to have a clear understanding of your organization’s needs and goals.</li><li>You’ll need to select the right CDP for your organization. There are a lot of options on the market, so it’s important to do your research. Once you’ve selected a CDP, it’s essential to get buy-in from all stakeholders and ensure that everyone is on board with the implementation process.</li><li>You’ll need to establish clear metrics to measure the success of your CDP. By following these CDP best practices, you can set your organization up for success with a CDP.</li></ol>

The key answer to this question is purely dependent on the stage your business is in. If yours is a brand-new business, improving brand awareness through customer acquisition is your highest priority.

Top 10 CDP Best Practices To Enhance Customer Experiences

CDP Best Practices To Enhance Customer Experiences

Customer Acquisition vs Retention: Which One is More Vital?

Customer Acquisition vs Customer Retention: Which is More Important?

One of the first things any organization has to do to stop dirty data from getting into the system is to set up a data-friendly company culture.Whether yours is a big, medium, or small-sized Enterprise, it is very important to have a culture to encourage the proper use of data quality and for its analytics.But the term ‘culture’ can be vague and intangible. So here’s a quick definition – the Enterprise head honchos need to constantly talk to employees at all levels about the use of data analytics and its benefits.This should also include getting across the importance of accurate data and the <a href="https://www.expressanalytics.com/services/data-cleaning-services" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">impact of dirty data</a>.What’s more, roles and tasks have to be assigned to designated members of the team; more so to those who will be responsible for ensuring the consistent accuracy of all incoming data.Data quality and its importance, and its link to data management cannot be stressed enough.Managers need to constantly emphasize to all team members that to make the right data-driven decisions, the first and foremost task is to get the correct data in.----------------------------- Grow your business operations using our data cleaning services &gt;&gt;&gt; <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">Let's connect </a>----------------------------- That’s also because the data gets connected from the master database across a company’s CRM, DRM, and other such services so data management requires a certain consistency across all. Wrong or poor data can even become dangerous for an Enterprise’s survival.By now, you would have also understood that monitoring incoming data for inconsistencies or other errors is not a one-off thing. It is always a priority.Once you have done all of this and are confident that the message relating to dirty data and its avoidance has gone down the file and rank, you can go ahead and make your investment in creating the processes, including the software and assigning the people to man them.Yet, do not forget, after this too, you will need to continuously monitor and better the quality of incoming data.<h2 class="ql-align-center">Here are Some Common Roles to Ensure Master Data Management</h2>There are 3 ways this can be bifurcated: You can have a 3-tiered structure comprising a data owner, a data steward, and a data manager. At first, these may sound like overlapping or similar roles, but they are not.<h3>For example, here’s what the data owner does:</h3><ol><li>Play a pivotal role in data domains</li><li>Defines data requirements</li><li>Preserves data quality and accessibility</li><li>Decides who in the team gets what kind of access rights and</li><li>Permits data stewards to manage data</li></ol>So the data owner operates on a macro level in the ecosystem.On the other hand, the data steward is actually the one who lays down the rules and the plans and then coordinates data delivery. He is the operations guy.Last in this change is the data manager. This guy operates at a micro-level in the Enterprise. He normally coordinates between the data owner and the technical part of implementing the plans.Now that you have the systems, procedures, and manpower in place, what next? Remember, a fruitful data quality and management project require a holistic approach.This is where the ‘How’ part comes in – how to go about ensuring consistent good data?To determine the quality of data, here are some aspects to look out for:Accuracy, completeness, adherence to standards, and duplication. A combination of IT software, hardware, and human resources will take care of this.Your designation team with the given infrastructure first needs to identify all the problem areas from where bad data is likely to come in. Remember, all this effort is towards establishing a single source of truth.Thereon, your Enterprise will then have to develop a data quality program, and with the help of a data steward, apply the business processes that ensure all future data collection and use meet regulatory frameworks and eventually adds value to the business at hand.The correct method of matching high data quality with technology is to integrate the different stages of the data quality cycle into operation procedures and tie them in with the individual roles.----------------------------- Grow your business operations using our data cleaning services &gt;&gt;&gt; <a href="https://www.expressanalytics.com/services/data-cleaning-services" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">Let's connect </a>----------------------------- <h3>Use of AI in manipulating large data sets</h3>In an earlier post, we had written how with the entry of AI, data stewards could now use <a href="https://www.expressanalytics.com/blog/ai-data-cleaning/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">data cleansing</a> and augmentation solutions based on machine learning (ML).ML and deep learning allow the analysis of the collected data, making estimates, to learn and change as per the precision of the estimates. As more information is analyzed, so also the estimated progress.While identifying where your data is lacking or erroneous, large data sets always present a problem. How do humans track say a million data points? And say, in real-time? But with ML getting into the mix, that hurdle, too, can be surmounted.AI can be used to detect anomalies in data sets by being “trained” to continuously track and evaluate data, even as the data is being processed.What is even more important is that an ML solution can detect and deal with data integrity issues at the very start of data processing, and quickly convert such vast volumes of data into dependable information.<h4>In conclusion:</h4>Tracking, analyzing, and correcting/updating incoming data will eventually help an enterprise in making well-informed business decisions, providing a single source of truth, and eventually increased productivity.Handling dirty data in analytics isn’t simply a technical fix—it’s a strategic need.Understanding how to clean dirty data not only improves your analytics—it lets your team act with confidence and saves time.References:<a href="https://orangematter.solarwinds.com/2019/01/24/how-to-clean-dirty-data-the-life-of-a-data-janitor/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">How to Clean Dirty Data – The Life of a Data Janitor</a><a href="https://www.dnb.com/perspectives/master-data/6-key-responsibilities-of-data-stewards.html" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">6 Key Responsibilities of the Invaluable Data Steward</a><a href="https://searchdatamanagement.techtarget.com/definition/data-quality" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">Data Quality</a>

How to prevent dirty data? To determine the quality of data, here are some aspects to look out for: Accuracy, completeness, adherence to standards, and duplication. A combination of IT software, hardware, and human resources will take care of this. Your designation team with the given infrastructure first needs to identify all the problem areas from where bad data is likely to come in.

How Data Quality can be Preserved? How can AI be used to do it?

Here’s How to Tackle Your Organization’s Dirty Data

<h1 class="ql-align-center">Even A B2B Business Needs A B2B Customer Data Platform</h1>Unlike a B2C company, a B2B company has companies and businesses, not individuals as customers. Not only that, a B2B enterprise has to deal with a lengthy and often intricate buying cycle involving multiple departments. Sales is never a straightforward, one-on-one process here.Hence, if you are a B2B company, you have to be forgiven for not having contemplated adding a customer data platform (CDP) to your MarTech stack, in the mistaken belief that it was only for B2C businesses. You couldn’t be more wrong.In fact, studies exist that B2B businesses, as buyers of a CDP, will multiply between 2020 and 2025.A CDP can play a major role in account-based marketing in a B2B business. It will help evolve a single source of truth, and with it, help identify buyers, create buyer segments, deliver targeted content; in short, deliver a successful one-on-one marketing campaign.----------------------------- How Oyster CDP can help in Predictive modeling <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">&gt;&gt;&gt; Speak to Us&gt;&gt;&gt;&gt; </a>-----------------------------<h2 class="ql-align-center">Are B2C And B2B Customer Data Platforms Very Different From Each Other?</h2>At a macro level, the answer is “no.” The underlying principle of both CDPs is the same: to provide a <a href="https://www.expressanalytics.com/blog/identity-resolution-shaping-modern-marketing/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">unified view of customers</a> based on the data available to make marketing and customer service highly effective.Where the difference comes in is in the strategy that both forms of CDPs help assist with. For example, in a B2B company, a CDP is at the very heart of its account-based marketing strategy. The platform is used to gain insights from their prospects’ data, say, for example, targeting a strategic prospect with a special offer based on a certain action by the latter. On the other hand, in the B2C world, CDPs are used to gather intelligence and to activate insights related to existing customers.<a href="https://www.expressanalytics.com/blog/how-to-choose-cdp/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">Using a CDP</a>, a B2B business can compile data from all its marketing and sales stacks, and third-party sources. This eventually helps B2B companies deploy smarter campaigns to grab enterprise accounts. Some B2B companies have reportedly increased as much as 70% higher engagement with fellow companies when using a CDP.<h3>What Capabilities Must A B2B Customer Data Platform Have?</h3>First and foremost, what any B2B CDP worth its price tag must be able to deliver is the wherewithal to map leads to accounts. Because as a B2B business, you’re selling to individuals in buying centers and accounts that live in hierarchies.<h4>Here are some of the must-have features of a B2B CDP:</h4>Integration with Sales and 3rd party sources: This is of primary importance because Sales must be able to effectively work on the leads passed on it by Marketing. Things must go beyond the simple sharing of data.Also, the CDP must be able to ingest and integrate data from 3rd party sources into unified profiles.‍Flexible: A B2B <a href="https://www.expressanalytics.com/solutions/cdp-users-vendors/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">CDP</a> should be able to connect with outside systems and data from any source. Never go in for CDPs that cannot do so. It is also vital that a B2B vendor is not linked to one specific platform but they need to be functional across your technologies.Scalable: There are cases where initially a B2B company may have to work low volumes of data, but a good B2B CDP must be scalable, i.e. must be able to enlarge in scope and size once the customer base increases.<h4>Oyster B2B CDP</h4>The Express Analytics Oyster CDP has all of the above qualities and more. It allows marketers to map user &amp; account details to help them run account-based marketing campaigns.So, for example, Oyster collects user IDs when multiple apps such as HubSpot, LinkedIn, etc. are connected to develop one single master profile. No more confusion about the identity of a contact. What’s more, you can even create the same profile for logged-in and non-logged-in users. All of which help eliminate duplicate contacts.Oyster b2b CDP also gives Sales &amp; Marketing the data to truly understand their customers to drive personalized engagement. It allows <a href="https://www.expressanalytics.com/blog/what-is-stp-in-marketing/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">customer segmentation</a> and audience management, be it lists of people or a list of accounts, at a drilled-down level, something not seen in other B2B CDPs.<h4> </h4>

A B2B Customer Data Platform help identify buyers, create buyer, deliver targeted content, create buyer segments, in short, deliver a successful one-on-one marketing campaign. It compile data from all its marketing and sales stacks, and third-party sources. This eventually helps B2B companies deploy smarter campaigns to grab enterprise accounts.

Even A B2B Business Needs A Customer Data Platform

Even A B2B Business Needs A B2B Customer Data Platform

<h1 class="ql-align-center">Analytics Dashboard and its importance</h1>When a year comes to an end, there’s always a tendency to look back at the days gone by to analyze what certain developments mean for a certain industry or sector.So, as the curtains are set to come down in 2020, we at Express Analytics, too, plan to bring you a roundup of all the prominent developments of the year in the world of data analytics. But that will be in another blog post.Today, though, we will look at a prediction made by none other than well-known research firm Gartner in late October and the intense debate it generated in the data analytics industry.In “<a href="https://www.gartner.com/smarterwithgartner/gartner-top-10-trends-in-data-and-analytics-for-2020/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">The Top 10 Trends in Data and Analytics for 2020</a>” report, Gartner laid out the top technology trends that data and analytics leaders need to focus on as they look to make essential investments to prepare for a reset.In it, it has virtually forecasted the end of “pre-defined analytics dashboards”, to be replaced with “dynamic data stories”.Said the report: Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration. As a result, the number of time users spend using predefined analytics dashboards will decline.The shift to in-context data stories means that the most relevant insights will stream to each user based on their context, role, or use.The Gartner team added that such dynamic insights would leverage technologies such as <a href="https://www.expressanalytics.com/blog/augmented-analytics-the-future-of-business-intelligence/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">augmented analytics</a>, NLP, streaming anomaly detection, and collaboration.The report was followed up with a series of articles on Medium and on other blogs, much in the same vein – “Analytics Dashboards are dying”. Not that this lot was saying something entirely new.For some time now, there have been similar predictions, on and off, claiming pre-defined analytics dashboards were “just not up to the mark”, and their end was near.Ranged against such naysayers are those who continue to insist (a) analytics dashboards are here to stay (b) dashboards do not really have a suitable replacement for now (c) notebooks are the best alternates for dashboards (for now, at least).When they first came into play, <a href="https://www.expressanalytics.com/services/business-intelligence-analytics-services" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">data analytics dashboards</a> represented a leap forward from the staid (and cumbersome) spreadsheet. Suddenly, visualizing and reporting complex data using interactive and, dare we say, colorful dashboards was so much better than the average, one-dimension spreadsheet.<h2 class="ql-align-center">Why the Problem with Analytics Dashboards Now?</h2>The way we see it here at Express Analytics, the foremost problem with analytics dashboards is context, or rather, the lack of it. The other is that “one dashboard does not fit all.”Let us not forget that with the increase in data democracy, dashboards today are used by two distinct categories of users – the data scientists/analysts, and then the “non-technical” users like the Sales and Marketing teams.But context is the paramount reason for the negative outlook on analytics dashboards today. Often, perspective is missing when dashboards are designed. Without it, a dashboard’s as good or as bad as your spreadsheet.Here’s an example: If you have a dashboard that visualizes the number of clicks and likes got on your company’s social media channels, you need to put it in perspective in the same dashboard.That perspective could be: how are the numbers in comparison to the previous month’s, or the same time last year, or how are they in comparison to your rival’s?A poorly designed analytics dashboard seems to be the main reason for detractors predicting its death. Ease of use maybe the other.<h2 class="ql-align-center">Pre-defined or DIY Analytics Dashboards?</h2>This brings us to the question – do DIY Analytics dashboards offer a better alternative to pre-defined ones? There’s no clear answer here, but we can offer some tips: everything depends on the requirements of the data project, the budget, and the profile of the end-users.Out-of-the-box boards often come with some expensive license fees, but if you have a special requirement there are always boards you can design using open-source code like Python, for example.But what’s even more critical is that the time has also come to move on from static&nbsp; analytics dashboards to those that provide actionable insights. Actionable insights cause action to happen rather than merely answer a question. Which means instead of the user spending valuable time to make sense of the visualization, actionable analytics dashboards can directly tell him about an insight.At Express Analytics, for example, as part of our customer data platform Oyster, we are currently building a sentiment analysis and voice of customer analytics service.Here, one of our aims is to develop an analytics dashboard that can directly tell the client that 40% of the negative reviews are for Product X because it’s over-priced. This, then, will serve as direct insight to the user which they can promptly rectify.For interactive <a href="https://www.expressanalytics.com/services/data-visualization" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">analytics dashboards, unlike say Tableau or PowerBI</a>, users can create data visualizations on the web using d3.js JavaScript libraries which give developers a more granular control of the visualizations.D3 stands for Data-Driven Documents. d3.js can thus become your preferred tool for data visualization.<h3>Notebooks: Are They the Ideal Replacement for Analytics Dashboards?</h3>For a couple of years now, data notebooks have been climbing the popularity charts, and some users have even started touting them as a replacement for the dashboard.Editor of Memory Leak <a href="https://medium.com/memory-leak/data-science-notebooks-a-primer-4af256c8f5c6" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">Astasia Myers</a> describes them as: Notebooks are a form of interactive computing, in which users write and execute code, visualize the results, and share insights.Notebooks are used by analysts and even non-technical users for exploration tasks. The versatility of a notebook has led to users demanding more by way of visualizations.But data enthusiast Axel Christ while writing in Medium says notebooks still face some challenges that need sorting. “I believe that Analytics dashboards have their place in a business context and are here to stay. At the same time, I would love it if the foundation they were built on would be a notebook-style technology”, he concludes in the article.<h4>In Conclusion</h4>As with any other technology, data analytics, too, is evolving. Analytics dashboards are certainly not the most optimal interface in visualization and reporting, hence, they cannot be the last word, even as data analytics gets more common-place and used by non-tech teams.There’s a case then perhaps for two types of analytics dashboards – one for the analysts and the other for those who are not. Market evidence certainly supports this view.In the meanwhile, if notebooks or any other form of data visualization tool come online that helps democratize access to data, even more, they could evolve and replace dashboards eventually. But for now, dashboards are not going anywhere. Perhaps insisting on adding context to the dashboards and making them easier to use could lead to more adaptability.

Analytics dashboards are certainly not the most optimal interface in visualization and reporting; insisting on adding context to the dashboards and making them easier to use could lead to more adaptability.

Analytics Dashboards: Pre-defined Or DIY Analytics Dashboards

Analytics Dashboards: Some Say The End Is Near, We Say Not So Fast

Data wrangling is the practice of converting and then plotting data from one “raw” form into another. The aim is to make it ready for downstream analytics. Here are the steps in data wrangling: 1. Data Discovery 2. Data Structuring 3. Data Cleaning 4. Data Enriching 5. Data Validating 6.Data Publishing

Data Wrangling: Definition, Steps, Importance, and Benefits

What is Data Wrangling? What are the Steps in Data Wrangling?

The customer data platform (CDP), along with the predictive model, provides valuable insights to combine your data and provide a single customer view of your customer journey. Know how to get actionable insights from customer data platform development.

Getting Actionable Insights From Customer Data Platform

How to Get Insights from Customer Data Platform (CDP)

To survive the new Third Party Cookie “cookieless” era, you must manage your first-party data effectively. Using first and zero-party data, CDPs can build personalized customer profiles, enabling you to meet buyers and prospects where, when, and how they want.

Importance of CDP in A Post Third-Party Cookie World

Role of Customer Data Platforms in A Post Third-Party Cookie World 

A customer data platform (CDP) is critical in the world of digital customer engagement. Understanding a customer’s behavior and what they do are important factors for any business if it wants to stay relevant.These days, because of a combination of factors, many companies, especially those that are consumer-facing such as <a href="https://www.expressanalytics.com/blog/ecommerce-analytics-tools/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">e-commerce sites</a>, have either bought or built their own CDPs.From a fistful of vendors say about 10 years ago, today, there are literally 100s of such vendors in the CDP market.CDP buying has been boosted by two factors. The Covid-19 quarantine periods globally literally forced thousands of businesses to go “digital first” overnight. Due to this tectonic shift in the market, digital channels became a more important part of the marketing mix.As a result, managing prospects and customer interactions across owned and paid digital channels became more important.Additionally, third-party cookies will soon cease to exist. The number of third-party cookies has decreased due to concerns about privacy.Ad platforms no longer use cookie-based targeting. Nowadays, companies rely on their own cookies (first-party data). And that again has led to companies flocking to buying CDPs.<h1 class="ql-align-center">Why is It The Right Time to Invest in Customer Data Platform?</h1>Now is the right time to invest in customer data platform architecture because businesses are recognizing the value of customer data and the importance of having a holistic view of the customer.In order to be able to leverage and drive optimal value from your customer data, you must be able to integrate it across all of your touchpoints with customers.Therefore, investing in a customer data platform is important for the following reasons:1. Global Business EnvironmentsMany companies today face complex global environments where one size doesn’t fit all and due to different regulations, cultures, languages, and levels of sophistication, you must adapt your technology and business processes. To be successful, you must be able to adapt as your business evolves over time, and in order to do this, your customer data platform must be flexible enough to adapt and respond quickly to global situations.2. Increasing Regulatory And Social RequirementsOver the past several years, there has been an increase in global regulatory and social requirements, so it’s more important than ever to have a common data platform that enables you to meet global regulations. Many companies in industries such as financial services, insurance, health care, and retail have to comply with these regulations. However, it is difficult to change and implement new regulations after the fact.----------------------------- Get Actionable Insights into Your Marketing Campaigns <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">&gt;&gt;&gt; Talk to Us&gt;&gt;&gt;&gt; </a>-----------------------------A good customer data platform allows your organization to develop and maintain a common digital data architecture that can flexibly capture and exchange information as required by regulations. <h3>For Which Companies Can Customer Data Platform Be Useful?</h3>A customer data platform can be useful for companies that want to better understand their customers and improve customer engagement.Depending on the needs of your organization, a CDP can help you answer many different types of questions and it enables you to better engage with your customers.If you want to improve your customer loyalty, for example, a CDP can help you identify new ways to better understand your customers and build upon existing sources of data.<h2 class="ql-align-center">What should Customer Data Platform Include?</h2>You need to consider your end users’ needs when choosing which types of data to build your platform on top of.Here are some questions you can ask yourself about your users:1. Does your organization collect a lot of data? If your organization collects a lot of data, like customers’ age, gender, and geographic location, consider a CDP that relies on these types of data. You will then be able to offer your users more personalized and contextual information.2. Does your organization have a small IT team?If your organization does not have an in-house data management or technology department, you may want to consider a CDP that is easy to implement and use. You do not want a CDP that requires a lot of work from your staff or IT specialists to set up and manage. Look for a CDP that has a free trial period to allow you to test out the product before you buy it.3. Does your organization want to leverage a cloud solution?Cloud-based CDPs are very convenient for your organization as they allow you to be more agile since you don’t have to download software or manage your data. If your organization is looking for a CDP that will help you reduce administrative work and costs, Cloud-based CDPs are definitely worth considering.A CDP’s role in breaking down data silos is to integrate with other marketing and customer-related systems to collect and manage customer data.This allows companies to have a more complete view of their customers, which can help them create more targeted marketing campaigns and improve customer service.<h2 class="ql-align-center">Key Questions to Ask Before Finalizing CDP</h2>Although the aim of this post is not really to help you decide on a CDP, very quickly, before you <a href="https://www.expressanalytics.com/blog/how-to-choose-cdp/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">choose the right CDP</a> for your business, you need to understand how you’re using data or planning to. How much data do you already have about your customers?Do you have an established marketing and CRM system that is tied to your existing systems, or are you just starting to get a handle on your customer data?What is your data governance process like?A lot of companies don’t know where their customer data is stored, or what policies are in place to make sure that their data is secure.-----------------------------Experience Next-gen and Powerful CDP Analytics <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">&gt;&gt;&gt; Talk to Us&gt;&gt;&gt;&gt; </a>-----------------------------<h3>Challenges You May Face While Using Customer Data Platform</h3>So you are one of those businesses that did not go through the motions and purchased a CDP all the while thinking that a customer data platform would “magically” resolve all your customer and marketing issues. Or build an in-house one.Now, you have started to realize that there are challenges in using the CDP; indeed to understanding just how the technology works.That’s where you need customer data platform consultancy, someone who will do some hand-holding for you to help you eke out 100% performance out of your CDP.There are growing cases of many companies failing to implement CDPs after buying one. Much of the challenge of deploying any technology is human.You need a team to help your business navigate the intricacies of your incoming data before going ahead and building your database. There are services out there that make building a modern data stack a breeze.So there are two ways of getting your hands on a CDP – either buy an off-the-shelf one or develop one in-house.You may be motivated to buy an off-the-shelf customer data platform due to many reasons, but it might not be the right fit for your business.What you need instead is finding an alternative that might eventually turn out to be relevant for your particular business.Investing in an off-the-shelf CDP will pay off when you are not trying to fit specific requirements, or are experimenting in a sense to understand whether that software will provide value for your business.Off the shelf, CDPs typically come built-in for integrations; integrations to the digital marketing ecosystem like Google or Facebook, and so on.Your business may or may not have in-house expertise in managing this plug-n-play. That’s where you will need to call in a consultant.On the other hand, choosing to develop these capabilities yourself or relying on different third-party tools would require a higher development effort and require time for some things that only need to configure within a CDP.<ol><li>Ensuring that the customer data platform is able to integrate with all the necessary marketing and sales applications used by the organization. There are several parts of the data warehouse that you will have to build, either by using the built-in connectors or using a third-party API to pull data from other systems. The first step to achieving seamless integration for your organization is to identify the full set of required integrations.</li><li>The next step is to map out the necessary processes and data flows so that the various systems become integrated. This will involve creating (or evaluating) all the data sources, integrating them, and creating the scripts that push data to the data warehouse and pulling it from the same.</li><li>The last step is to add the system operators and administrators (the people who actually use the data warehouse), in order to enable them to visualize and exploit the insights derived from the data stored within the system.</li></ol><h2 class="ql-align-center">Importance of end-to-end Customer Data Platform Solutions and Services</h2>End-to-end customer data platform solutions and services for your enterprise can help you to manage and understand all of your customer data, in a single system.This can make it easier to identify and target your most valuable customers and to create more effective marketing campaigns. Sometimes, a single platform can be the catalyst that makes your customer data more relevant and actionable.Ensure clients are aware of and benefit from the available features of Customer Data Platforms. Contribute to the design and development of the solution.Unify different data sources to build holistic customer profiles and unlock the full potential of the CDP.A comprehensive and consistent customer profile can be used across channels and across your entire marketing stack.CDP consulting will help you get the most out of your customer data management platform, including:<ul><li>Help you design your customer data strategy</li><li>Help you with your data marts</li><li>Drawing up a roadmap charting the use of the CDP</li><li>Help you with the actual implementation of Your CDP</li><li>Get all the integrations right</li><li>Help you create a 360deg view of every customer and help develop customer segments</li><li>Help with reporting and analysis</li><li>Provide maintenance and support</li></ul><h3>Do You Have Any Challenge Or Question Regarding Your Customer Data Platform?</h3>If you’re considering deploying the Express Analytics customer data platform (CDP) consulting services, you may have some questions about what we can do for you.Our team of experts can help you implement your CDP that meets your specific needs, and we’ll work with you every step of the way to make sure you’re satisfied with the results.&nbsp;Our CDP Solutions Are User-Friendly We work with businesses of all sizes. Please fill up this <a href="https://www.expressanalytics.com/contact-us/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">form</a> and we’ll get back to you.&nbsp; <h3>Are You Looking for A Customized Data Platform?&nbsp;</h3>Are you looking for a customized data platform? Contact us! We can help you build the perfect platform for your needs, tailored specifically to your data. Check out our platform compared to the alternatives.

With our customer data platform (CDP) consulting, you can get a unified view of customer data for cross-channel marketing and communicate with your customers in a more personalized way.


Best Customer Data Platform Consulting Services for B2B

Why You May Require Customer Data Platform Consulting 

<h1 class="ql-align-center">How Marketing is Strategy and Strategy is Destiny?</h1><h2 class="ql-align-center"> </h2>In an article in the December 2013 issue of the Harvard Business Review, Author Professor Niraj Dawar argues that today upstream activities – such as sourcing, production, and logistics – are being commoditized or outsourced, while downstream activities aimed at reducing consumer’s costs and risks are emerging as drivers of value creation and sources of competitive advantage.Today the locus of competitive advantage lies outside the firm and the advantage is accumulative -rather than eroding over time as competitors catch up, it grows with experience and knowledge.Since competitors can emulate, clone, copy, or source from the same suppliers and neutralize a company’s competitive advantage, the company has to look outside the firm for competitive advantage. How the market perceives you can be a strategic advantage.According to the author you can choose to compete with players of your choice, you can change the criteria on which you compete, and best of all your competitive advantage can grow rather than diminish.Understanding the customers’ wants and desires, their <a href="https://www.expressanalytics.com/blog/machine-learning-techniques-guide/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">buying patterns</a>, their socio-economic status, the importance they attribute to certain features or the convenience of procuring the product, the price they are willing to pay for it, all can be the foundation of your strategy. In the era of social media and mobility, the customer is sending you these signals through their expressions in social media and ratings on the web. Collecting these signals and analyzing them to arrive at your strategy and the next best action can lead to a sustainable competitive advantage. Experimenting with control groups, evaluating the behavior changes as you hold out your marketing messages to the holdout group can provide greater insight into the buyer’s real motivations. This can then lead to different strategies, Costco, for example, has a triggers and treasures strategy, so the things that you routinely buy such as bread, milk, and eggs are priced very low motivating you to go to the club every week, but once you reach the warehouse you are guided thru aisles stacked with seasonal items, high fashion items, exclusives that are only available for a few days and only at certain clubs, so if you procrastinate the first time and want to buy the item the next visit it is gone.You are also motivated to visit multiple clubs to discover what treasures are hidden there. This is a behavior modification technique that leads you to buy the treasures as soon as you find them for the fear of missing out. Leads you to visit the store more frequently, at multiple locations in search of things that you never knew you desired.Amazon has a convenience marketing strategy and has adopted the club membership strategy of Costco, so now it is more like Costco than Walmart. Be a member of Amazon Prime and you are guaranteed a 2-day delivery at no cost. By ensuring that your buying experience is par excellence, and removing the friction of delayed shipments, Amazon has lifelong converts – who are not just couch shoppers but mobile shoppers too. These customers are so comfortable with the buying experience at Amazon that they stand in the aisle in Best Buy, Target, and Walmart, compare prices, and order on Amazon, confident in the knowledge that 2 Day shipping means two-day delivery no excuses.These two companies don’t produce the goods that they sell, so product innovation doesn’t play a part in their success, but understanding their customers’ <a href="https://www.expressanalytics.com/blog/machine-learning-predicting-consumer-behavior/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);" data-faitracker-click-bind="true">buying behavior</a> is their innovation and strategy. Marketing is the strategy and strategy is destiny. Superior logistics and centralized buying are indeed a part of their success but understanding the customer drives these functions not the other way around. The entire organization is executing flawlessly to deliver the habit-forming experience to the customer.

Marketing Strategy: Today the locus of competitive advantage lie outside the firm and the advantage is accumulative -rather than eroding over time as competitors

Marketing is Strategy and Strategy is Destiny - Express Analytics

Marketing is Strategy and Strategy is Destiny

<h1 class="ql-align-center">What is Dimensional Modeling</h1><h2 class="ql-align-center"> </h2><h3>Profile Dimension (aka Junk Dimension aka Mystery Dimension)</h3><h3> </h3>Hello readers! I hope you all are enjoying the colorful spring! This time I am going to tell you a story about a new friend of mine, who lives on the Main Street of the Dimensional Modeling town and goes by a whole bunch of different names! Know more about what is dimensional modeling in data warehouse?Dimensional Data Modeling is a data structure technique utilized for storing data in a data warehouse design to advance the data retrieval. I am not sure how &amp; from where he got all these names, but, It Is What It Is … As <a href="https://www.expressanalytics.com/blog/how-to-improve-your-brands-net-promoter-score-nps" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Data Warehouse</a><a href="https://www.expressanalytics.com/blog/how-to-improve-your-brands-net-promoter-score-nps" rel="noopener noreferrer" target="_blank" style="background-color: transparent;"> </a>Architects, we usually know the two kinds, namely, Dimensions &amp; Facts, very basic, right? But then, every once in a while, we have our “encounters of the third kind”… the attributes that are neither dimensions nor facts! This new friend of mine helps us deal with these! &nbsp; Scenario: Last month, we kicked off a new project to build a new DataMart for the supply chain group here. Everybody’s calendar got filled with a lot of meetings, meetings to discuss the project requirements, meetings to chalk out the estimates &amp; the plan. Life was cool &amp; I was doing my most favorite stuff, data modeling for the new project. I came up with a beautiful design, right out of the pages of a Ralph Kimball book with 5 dimensions, and 7 measures, and I was on my way to the star schema heaven. Suddenly I stumbled upon the user’s awkward questions: – Where is such and such flag? Where’s the blah-blah type? Why can’t I see that XYZ code? Did I wonder if we really need all of those junk attributes for BI? Well, it turned out that those standalone codes &amp; flags &amp; types really meant a lot for the business.----------------------------- Know the Importance of Dimensional Model in Creating Data Warehouse? &gt;&gt;&gt; <a href="https://www.expressanalytics.com/contact-us" rel="noopener noreferrer" target="_blank" style="background-color: transparent;" data-faitracker-click-bind="true">Talk to Us</a>&lt;&lt;&lt;----------------------------- Traditional Approaches &amp; the issues: I had 2 options in my mind at that time to deal with this situation:<ol><li>Create new tiny dimensions for all of these attributes. But then, I was worried that my good-looking, picture-perfect model is going to get crowded with all these new dimensions that have nothing much to them other than just those codes, flags &amp; types.</li><li>Add all these transactional attributes to my fact table. But then, my fact table won’t just stand for 100 million rows of these sparsely populated attributes.</li></ol>I didn’t like either of the options. And then, like Captain America, this new friend of mine, the “PROFILE” Dimension, came in to save the world, or at least my model! Concept: A profile dimension is a dimension that holds all the unique or valid combinations of a set of columns, and assigns a unique key to each combination. This key is then hooked up onto the fact table. The set of columns that this dimension encompasses are usually low cardinality attributes like flags, types, codes &amp; statutes, etc. These attributes do not necessarily have a direct correlation or relationship with each other but are only housed in a single dimension table. <h2 class="ql-align-center">Example of Dimensional Modeling</h2><h2 class="ql-align-center"> </h2>Let me tell you more about the exact situation I was trying to resolve. We had a Purchasing transactional table from the ERP system that needed to be fed into the DataMart. Apart from the 5 dimensions &amp; 5 measures that I talked about earlier, this transactional table had several codes, statuses &amp; flags.All these standalone codes, statuses &amp; flags were moved to a profile dimension (dimensional modeling in data warehouse). Here is how it looks in the model. Please take a look at the profile dimension (dimensional modeling in data warehouse) which is marked in GREEN. Of course, this is a much-simplified version of the actual star schema, just to explain the concept.<h2 class="ql-align-center"> </h2><h2 class="ql-align-center">Advantages Of Dimensional Modeling</h2><h2 class="ql-align-center"> </h2>A profile dimension (dimensional modeling in data warehouse) allows all the columns to be queriable, while only adding one column to the fact table, and providing a much more efficient solution in comparison to either creating multiple dimensions, or leaving all the data in the fact table.By moving such transactional attributes to a profile dimension, you’ve got fewer indexes on the fact table which might be important depending on the size. Data Population: A key consideration when populating the profile dimension is, how many combinations are technically possible v/s how many actually exist in the data set. If the number of all possible combinations is too high, the profile dimension size may be unmanageable.Also, many of the technically possible combinations may not even make sense in reality. In such cases, populating only the combinations that exist in the data set makes the design more efficient.On the other hand, you are safe to create all possible combinations, if the attributes have a fixed set of values, like Boolean, or codes from a known finite set, because you can be sure you’ve created a dimension row for every combination that the data set might have. If there are free-form string columns, then you need to make sure your ETL can generate new dimension rows and surrogate keys as new combinations are created in the source system.As I mentioned earlier, this dimension is also called a ”Junk Dimension” or a “Mystery Dimension”, because it houses all those junk/mystery transactional fields that are neither dimensions nor facts. I hope you would find this new dimension table concept helpful in taking care of the outlier attributes in your data model… Happy Modeling!

What is Dimensional Modeling in a data warehouse? Profile Dimension (aka Junk Dimension, aka Mystery Dimension).

What is Dimensional Modeling?

What is Dimensional Modeling in a Data Warehouse?

A brand’s Net Promoter Score (NPS) is a key metric that specifies how likely your customers or clients are to recommend it to others.

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