Author: Franz Malten Buemann

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Customer Intelligence Platforms are the hottest buzzwords on everybody’s lips in the marketing world in 2021. From this article, you will learn what connects them to the Customer Data Platforms, and what makes a huge difference. And, most importantly, what value they are able to bring to your company.

 

As the Accenture survey shows, 48% of customers expect to make the brand feel special for being good customers. A proactive attitude and extremely personalized service are required. In 2021 solving problems with template solutions do not mean a delightful customer experience anymore. 

 

Though companies work hard to address the customers’ expectations, it is not always easy to achieve. Marketers and customer service need very detailed customer data to personalize their offers and activities. Data scientists need to deliver useful data for the marketers and customer service lightning fast, so they can help out the customers here and now. 

 

Systems like Customer Relationship Management (CRM), Master Data Management (MDM), Data Management Platform (DMP) were developed to address this issue. All of them had a similar problem, they stored data in silos and did not exchange it, so building a single consumer view, useful for marketers, was next to impossible. The introduction of the first-generation Customer Data Platforms (CDP) promised to solve this problem and become a single source of truth useful not only for marketers but across all the company. How did they fare?

 

 What are “classic” CDPs and where do they fail

 

The purpose of “classic” CDPs

 

Customer Data Platform is a digital tool that gathers and unifies first-party consumer data from multiple sources and combines them into a single, comprehensive customer profile.

 

A similar definition is provided by the CDP Institute: “packaged software that creates a persistent, unified customer database that is accessible to other systems.”

 

“Packaged software” means that CDP is ready-to-use, off-the-shelf software, provided usually by the vendor. 

 

The part about “persistent, unified customer database” means that CDP collects the data from many different sources, basically, all the company’s touchpoints, where acquiring first-party consumer data is possible, like sales, loyalty, customer service, social media, etc. Data from different sources is stored in CDP, then merged and unified into a single customer profile.

 

Finally, “accessible to other systems” means that customer data is shared with any other system that needs it, like those used by sales, marketing, commerce. 

 

So the Customer Data Platforms serve three purposes:

 

They collect and unify all the company’s first-party data

 

Most of the systems, like email or previously mentioned CRM, used by marketers operate in silos. That means the data stays within them and is not exchanged across the systems. This fragmentation obscures the big picture. CDP serves as a connection between the fragmentary sources and produces a single truth.

 

 They enable effective customer data management

 

CDPs enable the company to manage effectively first-party data in the context of privacy and data rights, by controlling what data is, under what consent is available to whom inside the company.

 

They enable data-based actions

 

First-party data is unified into consumer profiles. These profiles are then structured into audience segments. They can be then used across other platforms within the company.

 

The problem

 

With such a promise first-generation CPDs emerged in 2013. They were designed to unify consumer data and provide a single source of truth for all company’s divisions, to make the actions made inside the segments work in synergy. 

 

In practice, they proved to be too narrowly focused on marketing use and did not consider the entire end-to-end customer experience across the company.  In the October 2019 report “For B2C Marketers, Customer Data Platforms Overpromise and Underdeliver”  Forrester concluded: “CDPs lack crucial capabilities to solve for identity resolution, data hygiene, and cross-channel orchestration.”. Without these capabilities, CDPs “can’t meet enterprise B2C marketers’ expectations for personalized and targeted customer engagement.”

 

What was the source of the problem? The first-generation CDPs were technically able to gather data from all the sources the company provided, they also had the functionalities to build a single consumer profile. But to build this profile, all the data had to be manually analyzed by the data scientists. Only on the basis of their analyses, suitable actions could be taken.

 

And as Harvard Business Review discovered in 2018, up to 80% of the time is spent by data scientists just to organize and clean raw data to uncover meaningful information. A huge amount of work put into just organizing datasets leaves them with just 20% of the time to perform the actual analysis.  This was the aforementioned problem of data hygiene.

 

This leads to another area, where traditional CDPs fall short and that is providing holistic consumer profiles, useful across all the company, not only the marketers but also sales, customer service, loyalty etc. Pushed by the time limit, data scientists are only able to produce fragmented models. Then, on the basis of these incomplete models, the actions also had to be taken manually. 

 

There was a lot of data, but intelligence did not effectively emerge from it. This is when CIPs entered the stage.

 

Customer Intelligence Platforms, the next generation of CDPs

 

Customer Intelligence Platform (CIP) is the next step in CDPs evolution. CIPs include zero-party data along with first-party data to provide insights. And they leverage AI and machine learning to understand, resolve and evaluate both structured and unstructured data available to the company.  

 

Solving with AI the identity resolution, data hygiene, and cross-channel orchestration problems, that the “classic” CDPs had, include:

 

Resolving and de-duplicating core master data about prospects, customers, accounts, locations, transactions, preferences, and associated reference data.
Matching data entities and new record types.
Enriching the first-party data with zero-party indicators. 
Allowing a wide range of users to perform complex analysis via a seamless interface.
Generating multiple unique customer views in real-time.

 

CIPs use AI and machine learning to gather, analyze and evaluate qualitative and quantitative data. They are able to share insights with marketing, sales, customer service, financial, etc. way more effectively than “classic” CDPs were. Adding intelligent automation removes consumer friction points by streamlining data-driven actions and allows to monitor every step of the customer journey. On this basis, predictive customer behavior models are created. 

 

Examples of effective cross-channel orchestration:

 

An issue is reported to customer service. CIP informs the service that this is a high-value client to the company that has just made a large purchase.
An issue is reported to customer service.  CIP informs the marketers to exclude this client from the planned campaign until the issue is resolved, to prevent irritation. 

 

From this standpoint, CIPs are a modern iteration of CDPs, backed by AI and machine learning. Technically speaking, SALESmanago is a Customer Intelligence Platform. We however use the term AI Customer Data Platform with Omnichannel Execution. Next-gen CDP would also describe us accurately. All these terms are technically correct.

 

Benefits the CIP may provide your company with

 

Customer Intelligence Platform provides the company with:

 

 Single consumer view across all the divisions

 

Connects all the devices and collects all the data from all planned touchpoints like which consumer is looking for what, how much time do they spend on searching, what are the most frequently visited places.

 

 Effective Segmentation

 

A single consumer view enables effective segmentation of the audience. AI then further helps to choose the right audience for the campaign. 

 

Enriched  consumer data

 

First-party data is enriched by zero-party data to build a comprehensive insight into a consumer.

 

Unparalleled customer experience

 

AI and machine learning are able to analyze multiple-source data with a speed impossible to achieve by data scientists. It also automates the delivery process across all the channels, ensuring a hyper-personalized, omnichannel customer experience.

 

This in turn results with:

 

Boosting customer loyalty

 

Customer Intelligence Platforms help the company in gathering data relevant for understanding the customer needs and activities. Understanding results in developing the experience that the customers will value. The satisfaction provided by the brand will increase their loyalty.

 

Increasing business agility

 

The Decision-making process and response time can be shortened thanks to real-time access to customer insights.  A brand can respond quickly to changes in the internal and external environments without losing its vision and momentum.

 

Building a real and strong relationship

 

Understanding customers’ needs and values creates a deep and meaningful connection between them and a brand. It makes the interaction more personal, relevant, and consistent.

 

Streamlining marketing efforts

 

All the brand’s efforts to understand the customers and act with relevant reactions are more effective with Customer Intelligence Platform. It also minimizes the cost of all the actions.

 

Creating a competitive advantage

 

Much more differentiated customer experience provided by the Customer Intelligence Platform better suits the needs of the customers. The brand has the means to establish an edge over the competition.

 

Wrapping up

 

From this standpoint, you can call the rise of the Customer Intelligence Platforms a promise made by CDPs finally delivered. AI and machine learning unlocked all the potential that was in the CDP idea from the start.

 

No wonder that 83% of marketers plan to involve AI in their 2021 strategies to provide a more meaningful customer experience. Not only do the majority of the marketers plan to include it into their strategies, but 84% of them also try to develop such capabilities in-house. This however may prove difficult. The companies should take into consideration:

 

cost factors of such operation 
high shortage of AI talents. 

 

Both hiring in-house AI talents and tasking them with building custom AI solution will generate a significant financial burden for the company, as the experts point out. In order to judge it for yourself, it would be wise to assess the vast possibilities of the AI Customer Data Platform with Omnichannel Execution. Request a SALESmanago demo and learn the value we may provide to your company.

As a marketer or business analyst, you know that data is an important part of your success. And the way you store and organize your data will either make your job easier or harder.

There are many ways that you can store data, one of them being data warehousing. This is an excellent option for businesses that need to look at a large amount of data from multiple sources. Today, let’s learn what a data warehouse is and how it can help you analyze your data.

With a data warehouse, you can perform queries and look at historical data over time to improve decision-making. The main people in a company who will use data warehouses are data scientists and business analysts.
A data warehouse will get data from multiple sources, including relational databases or transactional systems. To access the data, analysts will use business intelligence tools to analyze, data mine, make visualizations, and conduct reporting. As data continues to evolve, it’s imperative for businesses to use data to stay competitive.
What is the ultimate outcome of a data warehouse?
The ultimate outcome of a data warehouse is to extract insights, monitor performance, and improve decision-making. By using reports, dashboards, and visualizations, analysts have all the tools they need to make the right decisions.
Benefits of Using a Data Warehouse
1. Historical data.
One of the main benefits of data warehouses is the ability to look at a large amount of historical data over time. With a data warehouse, you can consolidate a large amount of data from many sources to better inform your business decisions. Looking at historical data will allow you to analyze trends over time and strategize effectively.
2. Data from multiple sources.
Additionally, with a data warehouse, you’ll be getting data from multiple sources so you’ll have a more complete picture when it comes time to analyze the information. With something like a data mart, you only get data from a single subject, as opposed to data warehouses that are meant to process and organize data from multiple sources.
3. Stability.
Data warehouses are also more stable sources of data that you can use to look at data at a high level or a granular level. This gives you the flexibility to look at data closely and perform queries quickly. A data warehouse will have high-quality data because it’s coming from multiple sources, it’s consistent and more accurate.
What Data Warehouses are Not
When you first hear the term “data warehouse,” you might think of a few other data terms like “data lake,” “database,” or “data mart.” However, those things are different because they have a more limited scope. While they might perform a similar function, the structure is different. Let’s dive in below.
Data Lake vs. Data Warehouse
A data lake stores unfiltered data from multiple sources to be used for a specific purpose. This means that you’re looking at raw data from something like social media or an app. The datasets are built at the time of analysis. This is low-cost storage for unformatted, unstructured data.
On the other hand, data warehouses are used to analyze and process data. In a data warehouse, the data has already been gathered and contextualized and is ready for analysis. Ultimately, it’s a more advanced data storage tool that can use large amounts of historical data.
Data Mart vs. Data Warehouse
A data mart is a subset of a data warehouse. Usually, they’re designed to easily deliver specific data to a specific user for a specific application. Data marts are single subject in nature, while data warehouses cover multiple subjects.
Database vs. Data Warehouse
Databases are often confused with data warehouses because they serve a similar purpose. However, the difference is that databases are not meant to perform analytics on a large collection of data. Databases are used to record and retrieve data while data warehouses are meant to analyze large amounts of data sets. Think about it like this: data warehouses store data from multiple databases.
Data Warehouse Architecture
A data warehouse architecture is a method you use to organize, communicate, and present your data.
You can use a basic architecture, a staging area, or a staging area and data marts.
This means that you can have a data warehouse get its data and then have the users look at reporting and analysis. Or you can have the data broken down into data marts before users look at the analysis and reporting.
The staging area you see in some of the images below is used to clean and process data before putting it in a warehouse. This simplifies data preparation. To get an idea of what each of these looks like, take a look at the images below.

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Data Warehouse Software
1. Snowflake Data Warehouse

Snowflake data warehouse is a data platform built on the cloud infrastructure. This is a great option for businesses that don’t have the resources to support in-house servers.
With Snowflake, users can pay for storage and share data easily. You can mobilize data seamlessly across public clouds as data consumers, data providers, and data service providers. This software will help you democratize data analytics across your business so all users with varying expertise can make data-informed decisions.

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2. MarkLogic

With this data warehouse solution, you can perform complex search operations with different types of data including documents, relationships, and metadata. MarkLogic is a fully managed, fully automated cloud service to integrate data from silos.
3. Oracle

Oracle Autonomous Data Warehouse is a fully managed database tuned and optimized for data warehouse workloads with the performance of Oracle Database. It delivers a new, comprehensive cloud experience for data warehousing that is easy, fast, and elastic.
While data solutions might seem overwhelming, they’re important for your day-to-day business decisions. With a data warehouse, you can simplify your data storage, management, and analytics.

Keeping track of expenses as a business owner can be taxing. You have to document every detail to make sure you stay within your spending limits while promoting your products or services, delivering on promises, and developing new offerings.
A business budget worksheet can help you stay organized.
Having a template to work from will cut down on the time it takes to write down the details of a budget, help you prioritize projects and allocate resources to get them done, and reveal trends of the money you spend versus the results achieved.

Depending on the complexity of your company, you may need to oversee a number of individual budgets while managing the overall spend. The business budget worksheets below range from specific templates — from product marketing to website redesign — to comprehensive ones that cover all aspects of your marketing plan.
Let’s dive in so you can take control of your budget like never before.
How to Write a Business Budget
1. Use Budget Templates
Creating a business budget from scratch can be overwhelming—you need to capture the details of each month’s projected budget, actual spend, and the cumulative total of each.
If you’ve never written a business budget or are looking for a specific marketing worksheet, you can start with HubSpot’s Marketing Budget Templates. This download includes eight well-designed and detailed templates to easily manage your finances, with options for Microsoft Excel or Google Sheets. A quick overview explains how to use each template so you can easily start filling in your own information.

Download Now
2. Set Your Strategy and Goals
To make the most of your budget, you have to know what goals you want to achieve and the strategy to get there. If you’re working to bring in more sales (a goal) and plan to improve your website to attract leads (the strategy), you’ll have to put funds towards the redesign project.
Check out these strategic planning models that can help map out your long-term goals if your business is just getting off the ground. That way, your budget will reflect the financial resources needed to accomplish your objectives.
3. Gather the Numbers
Every company has different needs, so no one budget will be exactly the same. A branding and creative budget, for example, will have vastly different line items than a website redesign budget.
No matter what budget you’re putting together, you’ll need all of the relevant expenses for a comprehensive overview. Here are the basic numbers you may want to include:

Revenue projections: Consider your historical financial performance and projected growth income.

Fixed-cost projections: The costs that don’t change (i.e. employee compensation, office rent, business software, insurance, and utilities).

Variable-cost projections: The costs that may change month-to-month (i.e. overtime compensation, supply costs, or software that varies by usage).

Annual project expenses: The cumulative costs of implementing all of your company goals for the year.

Individual project expenses: The costs associated with each project, which should be tracked in individual budget worksheets.

Target profit margin: A ratio that reveals how much money a company makes. Knowing your bottom line — and including it in your budget — is a helpful reminder of what you hope to achieve within the year and a good benchmark when analyzing your monthly financial trends.

Depending on the budget, you can also include cash, inventory, accounts receivable, net fixed assets, or long-term debt.
How to Manage a Business Budget
No budget is an island. All companies are impacted by poorly-managed budgets, especially a small business just starting out.
When your budget is just one piece of the puzzle, you’ll likely need to get it approved by a manager or executive team before spending any money. If you’re running a business on your own or with a small team, it’s smart to find a trusted colleague or financial expert to look over your numbers. They may be able to point out areas to cut costs, reallocate funds, or create larger profit margins.
Want to make sure you’re on track? Figure out how much you should put aside for a marketing budget that meets your goals.
Once your budget is in place, checking in on it once a year isn’t enough — you need to review it monthly (at minimum) to make sure your expenses aren’t out of control. Once you set your annual budget, revisit it at the beginning and end of every month. If you like to be in the know, you can even set a time to review it mid-month to double-check that everything is on track.
When a new project pops up, simply add it to your existing business budget worksheet and make adjustments to the overall expenses. The same thing applies if you wind up dropping a project. Company priorities change constantly, and your budget needs to adapt along with the shifts.
Business Budget Worksheets for Small Businesses
You poured through past financial records, made future projections, mapped out your upcoming projects, and have all of the information you need to build a well-rounded budget. Now it’s time to choose the best business budget worksheet for your goals. Luckily, all of these options make it simple to stay on top of your finances.
HubSpot Marketing Budget Templates
If you want a worksheet for each marketing niche, HubSpot has you covered. One download gives you access to eight budget templates: a master marketing sheet, product marketing, content, paid advertising, public relations, branding and creative, website redesign, and events.

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Small Business Budget Templates
Simplicity is the theme of these business budget worksheets by Smartsheet. Each Excel template is free to download, with options for multiple products, business expenses, startups, and more.

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Business Expense Template
Need a polished business expense budget? Microsoft Office has you covered with this well-designed Excel template that outlines costs for employees, marketing, office space, travel, and training. Just fill in the blanks and send it for approval.

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Year-Over-Year Budget Template
For a simple look at how your incomes and expenses change from year to year, this Excel template from Quickbooks is all you need.

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Freelance Budget Templates
Working for yourself often means combining personal and business expenses. That’s why these Excel templates from Business Load include income projections alongside personal costs. You can even budget what you’ll contribute to taxes, your 401k, and emergency fund all in the same sheet—because you likely have more than enough to manage.

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Sample Business Budget Worksheet
Personally, I’d rather endure the monotony of writing lines than spend all day organizing numbers in a blank spreadsheet. But having an example to work from makes it easier to make sure everything is on track. If you share that mindset, here’s a filled-in sample of a business budget worksheet to get you started.

The sample shows the budget needed for a website redesign project, with each expense categorized to keep it organized and easy to read. You can see where the budget went over (UX testing) and where savings happened (CMS software).
Setting up your own business budget using these templates is so quick and easy, you can have your numbers in order in no time. The sooner you begin, the better off your budget (and business) will be in the months and years to come.

Last Updated on October 14, 2021 by Rakesh Gupta Big Idea or Enduring Question: How do you deploy Flows or Processes using the Packages?   Objectives: After reading this blog post, the reader will be able to: Understand how to use packages to deploy flows Understand how to use packages to deploy processes Deploy
The post Getting Started with Salesforce Flow – Part 73 (Distribute Flow(s) or Process(es) Using Packages) appeared first on Automation Champion.

Last Updated on October 14, 2021 by Rakesh Gupta Big Idea or Enduring Question: How do you deploy Flows or Processes using the Change Sets?   Objectives: After reading this blog post, the reader will be able to: Understand how to use change sets to deploy flows Understand how to use change sets to
The post Getting Started with Salesforce Flow – Part 72 (Deploy Flow(s) or Process(es) Using Change Sets) appeared first on Automation Champion.

I was thinking of finding some group on linkedin, grabbing those users, then data mining for their emails? I’m not a marketer so I’m learning. My plan was to do a cold email marketing campaign using close or reply. I’m selling “premium/onshore custom software development services” for HIPAA compliant application, etc Let me know what other information I’m missing that could be helpful in providing advice, and i’ll get it right into the OP. Appreciate your patience with a noob.
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