Keep pace with our new releases to always get the most out of Data Talks CDP. See our new features, updates to the existing ones, and things we’ve fixed.
Keep pace with our new releases to always get the most out of Data Talks CDP. See our new features, updates to the existing ones, and things we’ve fixed.
Your feedback is of extreme importance and value to us and we have been working with full focus to deliver new features that will allow you to offer a top-notch personalized experience to your customers. After we have collected all your data and unified it and before targeting your customers and communicating with them, you would like to understand more about your customers, the segments that they belong to, and how performant your marketing efforts are. Data Talks CDP is providing you with the possibility of Self-service Data Exploration and Analytics functionality, without the need of involving any Data Scientists or Analysts from your team.
We designed an Analytics tool, which you can use to create reports and dashboards to analyze your customers, segments, marketing efforts, and so on, according to your most important KPIs. At Data Talks CDP we believe that understanding your data and showing its value, is even more important than the data itself.
On top of the insightful Analytics we provide you by default, you can evaluate your customer’s performance, how your Audiences are performing on certain KPIs, or how efficient your communication with your customers is by creating your own analysis using our Analytics framework.
One of the core functions of a CDP is to be able to target the right audience with the right offer. The first step to achieve this goal is to unify all customer-related data, to build a complete Profile view. The second step is to be able to separate your customers into audiences of Profiles with similar characteristics, preferences, and behavior. By doing this, you can build a separate communication strategy with each of those audiences and provide a better, more relevant, and highly personalized experience. In Data Talks CDP, we offer a pretty easy and user-friendly way to segment your customers, to share this information with any of your other systems, and to start acting right away.
In Data Talks CDP, we believe in flexibility and free hands! We want you to be the master of your data and to achieve what is most important for your organization. For this reason, we are always looking to provide you with the ability to configure things the way you want. The Segmentation Builder is one of those features. You can decide on your own what attributes you would like to include as Rules in the Segmentation Builder. And those are the attributes that you and your colleagues are going to use in order to create segments.
Using the Segmentation Builder, Data Talks CDP allows you to segment your customers into audiences with similar characteristics and act in your system or app of preference. In addition, in Data Talks CDP you are also able to act right away using our awesome Email Builder. With our Email Builder, you can create your next email sendout, pick one or more segments of customers to act on and create a well-designed and personalized email template, without needing any prior knowledge in HTML code. And the best part is that you can use any of your data stored in the Data Talks CDP in your Email Builder, to achieve top-notch personalized communication.
Some of the most important KPIs come from your Marketing Automation and email efforts. After you communicate through email or SMS with your customers, you want to check the results of your efforts. A first step to understand this is to track if your users are opening and clicking on the emails you are sending them. Those figures will help you understand if you are on the right track or if you need to change your marketing strategy. We are aiming to present those figures, showing you how many emails a specific customer has received, opened, clicked on, and how those figures compare to the rest of the Customer pool. We are, therefore at the moment, developing a placeholder in the Profile Overview page to capture those very important KPIs.
In order to boost the personalized experience for your customers, you want to know as much as you can about them. One of the most important and tricky parts for you to know is if and in what way your customers are related to others in your customer base. With Data Talks CDP you will be able to track this down and excel at your communication. We are developing a feature with which you will be able to see the Profiles that each customer is related to, what their relationship is, and if there is a way to measure this relationship.
For example, if you are attending an event regularly and you usually buy tickets for that event, not only for yourself but also for other people then you are building a relationship with them. They are becoming your event companions! By tracking down those relationships you can provide more personalized offers that will have affect more than one customer.
A very important aspect of a Customer Data Platform is consolidating segregated data from online and offline sources for the sake of creating a unified 360-view Profile. With our brand new web application, we are providing a very detailed and granular view of your customers, allowing you to make better and more accurate decisions. You will be able to check all the Profiles you store in the Data Talks platform and go into specific ones to get more details.
As a very first step to providing our customers with a detailed 360-view of Profile, we have designed and developed a placeholder where all basic details of a particular Profile are displayed. The list of details will be dynamic and it will fit the needs of every customer in the mindset of bringing your data into the Data Talks platform. The goal of this element is to provide you with a basic demographic overview of the Profile you are looking into.
Each one of your customers is performing, at some point in time, transactions within your business. They are purchasing products, booking and attending an event, increasing their membership card balance, and so on. All those events are collected in Data Talks CDP to create a more detailed view of your customers’ Profiles. We make it very easy to track all events for each one of your customers sorted on the date that the events took place so that you can follow the customer journey. Events are listed by Event Type, Event Description, and Date of creation. By clicking on an event you can get all information that describes this particular transaction.
For your convenience, we have created a placeholder in the Profile Overview section that holds the last five events of your customer. It gives you a very quick, yet detailed overview, of what the customer did lately, and by clicking on an event you get the full details behind the corresponding event.
One of the main tasks you want to do in a Customer Data Platform is to track how your customers are performing related to a set of important KPIs. By tracking those KPIs you can change your targeting and tactics to focus on what is most beneficial for your business. In Data Talks CDP, you can keep track of those important KPIs, not only on an aggregated level but also on the particular Profile level. On the Profile Overview page, you can get information about how a customer performs related to a set of KPIs. Those KPIs are tailored to your business needs and you are free to change and replace them anytime you like.
With Data Talks CDP we are helping you to bring your data from different online and offline sources and we make sure to unify this data to build a complete view of your customers. Customers’ data can be gathered from various third-party systems, mobile devices (iOS and/or Android), desktop browsers, and many other sources. Your customers, most likely, have unique IDs in all those systems and we need to consolidate those IDs into one when we are sure that they are referring to the same person. In the Identities tab under the Profile Overview, we are simply presenting all those Identities that we have gathered from all the different systems and devices for each one of your customers.
Data Talks CDP has three main data entities: Profiles, Events, and Inventory. Your customer is represented by a Profile on our platform. The transactions that a customer does with your business are represented by Events. Those events can contain one or more products, or other entities like stores, that are shared among Profiles and Events. Those make up the Inventory data. Often you might want to check details about your day-to-day business without looking at specific Profiles. For that reason, we have created a page that contains all events sorted by Date of creation without necessarily looking at a specific Profile. This is an easy way for you to validate that events you send to Data Talks CDP are being properly ingested.
Our end users can visit our Web Application to access dashboards with their data and act through them. Customers can now access our portal by using the Google Account of their organization.
Data Talks web application is the place where marketers, business analysts and data scientists interact with their organization’s data. We are offering a set of advanced analytic dashboards to get a detailed grasp of the data. End users are getting access by creating an account and today they have access by default to all the content of their organization account in the Data Talks web application.
However, there was a need to separate the dashboards by business area (Sales, Marketing, Finance), or other logical groups that only certain users can get access to.
We just launched a User Management console in which the Administrator user of our customer can invite other users within their organization, and define the permissions about the content this particular user will have access to.
Data Talks is hosting an SFTP server to which customers have access and can upload data in files.
However, there are some cases that the customers cannot automate the process of generating and uploading files to our SFTP server. In this case, and we will fetch the data from the customer’s SFTP server.
We are developing an integration in which we can connect to an SFTP server and fetch the data that needs to be fetched on a scheduled basis.
One of the most popular methods of getting data from customers is through files. Customers create files that contain snapshots or incremental data. The most preferred format of those files is the CSV one. Today we have developed code that tries to guess the parameters of the CSV format of the file like encoding, delimiter, escaping characters etc.
Although this method has served us well so far, we found out that this process may not be enough to cover the diversity of the configuration settings of the file. Thus, we are currently developing a feature to drive the process of discovering the settings of the CSV file by using metadata.
Υοu will be able to define the name of the file that will send over to us, together with a set of parameters that will describe how the file is delimited, how special characters are escaped, and what is the encoding of the files.
At Data Talks we believe in transparency and we are planning to develop a set of features to increase the transparency even further. One of those features we recently launched is the internal customer data processing alerts.
The purpose is to increase transparency about any potential issue that may affect the smooth customer experience. You as the customer do not need to act on the alerts, since our support team is on top of it and takes care of the issue.
As part of our product offering, we have the possibility to add a very important feature that will assist our customers’ decision-making process and answer important business questions. We call this feature Ad-hoc Analysis and a component of that feature is Exploratory Data Analysis & Insights.
Exploratory Data Analysis (EDA) is the process of analyzing and visualizing data to extract insights from it. Important characteristics of the data are revealed and the customer gets a better understanding of their data.
Exploratory Data Analysis & Insights is about:
• Increasing insight into a dataset
• Uncovering the underlying data structure
• Extracting important variables
• Detecting anomalies in data
• Testing assumptions
This is the process we are following:
1. Exploration of data. Looking for relationships between the data points. Exploring anomalies like duplicates, incorrect data types, missing data (nulls or empty strings) and any kind of suspicious observations. The results are communicated back to our customers to make sure that the data is correct and that no bugs are causing the outliers.
2. Analyzing using statistical models. Employing statistical models and algorithms to analyze your data and get full insights.
3. Data storytelling. Presenting the findings back to the customer in a way of data storytelling, as well as having discussions with customers to answer business questions or find new data points to look closer at.
Data Cataloging gives us deep knowledge about our customers’ data, not only in the Data Warehouse but in the Data Lake as well. Cataloging allows us to govern our Data Lake in a thorough manner and be on top of the data that exists in our Data Lake and where exactly that data is. What does this mean for you?
A Data Catalog can inform, and help prevent misuse of personal sensitive information, as well as provide documentation in case of an audit. In short, a Data Catalog provides a method to search and discover data in a way that is consistent with relevant regulations such as GDPR.
Data Profiling is the process of examining the data available in our Data Warehouse and collecting statistics and informative summaries about the data.
The main benefits of Data Profiling are:
1. Better data quality and credibility. Quality problems and anomalies in data are identified and communicated back to the customer.
2. Proactive crisis management. Profiled information enhances pro-activeness. Small mistakes in data can be stopped before they get bigger.
Below is a set of methods we use for our Data Profiling process:
1. Completeness Analysis. What is the ratio of empty, null and populated data in a field?
2. Uniqueness Analysis. How many unique values can be found in a given attribute across all records?
3. Range Analysis. What are the minimum, maximum, average and median values found for a given attribute?
With this feature, you can filter on specific Segments (tags) in Data Talks CDP and then target the audience you want to reach using your preferred marketing automation tool (Salesmanago, in most cases). You decide who you want to reach using our CDP and then apply tags on this audience, which automatically will be reflected in your marketing automation tool.
For example, an e-commerce business can segment their customers based on the category of products (cameras, mobile phones, laptops, etc) that are most purchased and on the brands customers prefer to buy. Then they can go into the marketing automation tool, filter on specific tags, and run highly targeted marketing campaigns.
To be fully GDPR compliant we started implementing a set of techniques to reach the goal of high Data Privacy in our Platform. The latest techniques implemented are: Natural Key (ID) masking and separating sensitive and non-sensitive data.
What is Natural Key Masking? Natural Key Masking is the process of assigning a Natural Key of a physical person (customer) to a totally random (surrogate key). We developed this technique to ensure that if we are asked to delete all sensitive data about a customer, we still have the customer in our data models with an artificial ID that cannot point us to the actual physical person.
Note: Natural ID:s can sometimes be email addresses and National ID numbers. In these cases, we need to also delete the ID, but we make sure to keep the non-sensitive data connected to this person such as purchases and website visits.
Another feature that we introduced together with API Blackboxing is API Data to Platform. This means that we’re able to take care of the data as soon as it arrives at our API gateway so we can add it to your data model. What does this mean for you? It means that we can process the data to fit the business and technical requirements you need.
Our API is now upgraded with a new cool feature. Blackboxing allows us to buffer all incoming data in case there is something not functioning on the receiving side. This means that data will never be lost on the way to the end destination and you will be able to track what was sent to our API and when we received it. What does this mean for you?
We have now created a Sports Data Model that caters to the needs of the sports industry. This gives you as a sports customer the ability to manage the entire customer journey and get a full 360° view of your fans in one place. What does this mean for you?
You can now elicit top-notch insights about fans’ engagement, loyalty to the club, ticket sales, revenue figures plus more – and act on them in time for the next game.