Name: Dynamic Customer Profiling - SAP Marketing Cloud
Uploaded: 2018-2-22
Duration: 744 s
Description: This video will give you a glimpse into how SAP Marketing Cloud creates a unified customer profile across channels to give you valuable insights into customers' real-time intents.

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<div><div><div><div><div><div><div><div><div><div>This video will give you a glimpse into how SAP Marketing Cloud creates a unified customer profile across channels to give you valuable insights into customers' real-time intents. </div><div><br></div></div></div></div></div></div></div><br></div></div></div>

Dynamic Customer Profiling - SAP Marketing Cloud

Hello! In this video we’ll look at how SAP Marketing  Cloud helps you to get a holistic view of your customers. The SAP Marketing Cloud offers a set of  capabilities to enable businesses to enrich  customer profiles across all different sources into a single view. It allows you to gain insights into customer’s real-time intents with predictive capabilities,  and then turn these valuable insights into informed, strategic, and profitable actions.  SAP Marketing Cloud dynamic customer profiling empowers you to build a consolidated  profile that merges data from multiple channels creating a 360° view of customers. This allows you to have a holistic view on the  customer base, including known and unknown customers. Here, we’re talking about collecting both  structured and unstructured data from internal and external sources.   For example, your first-party data about  purchases, loyalty data, events, social media interactions, or clickstream.  SAP Marketing Cloud collects all these data  and combines them to enrich existing customer profiles or to create new ones. What’s more, using natural language processing, you can derive the interests and  contexts from the data. At the same time, Dynamic Customer Profiling  helps you to adhere to data privacy regulations in the European Union.  With powerful, intuitive, discovery and visualization capabilities,  the SAP Marketing Cloud Dynamic Customer Profiling makes it easier to discover hidden trends and important insights into customer behavior and patterns. You can see what triggers customer activities in various customer journeys, and accurately  define the best audiences in an effective way for your marketing engagements. SAP Marketing Cloud is designed to enable omnichannel marketing activities.  Marketing relevant information is collected into  an overall profile covering all the different  identities of consumers and customers in the  various channels including Mobile, Web, Commerce, Social, CRM, etc.  This enables businesses to address their  consumers and customers holistically and  consistently across all channels by using the  marketing execution capabilities of the SAP Marketing Cloud. Now let’s look at the business applications  within the Dynamic Customer Profiling scenario of SAP Marketing Cloud.  Let’s start with an insight into all contacts and profiles.  The 'Contacts and Profiles Overview' app  provides you a high-level overview of relevant  customer information and helps to optimize individual engagement.  Here, I have quick access to relevant  applications like the Profile Dashboard or Contacts App.  At a glance, I can see the number of contacts  I’m allowed to contact and the channel through which they can be reached.  I can further see how engaged my contact base is and which interactions have occurred most frequently in the last 7 days.  Let’s move on to the Profile Dashboard.   In the Profile Dashboard application, I can view and analyze contact data. It’s a powerful dashboard which is always updated in real time.  The top summary section provides an overview  of the contacts across different levels, which can be freely defined.   I can see that my contact base is increased by  6,000 and nearly 3,000 of them are verified contacts. The tag cloud in the middle provides a glance of what my customers are interested in. The larger the font, the greater the interest.  I can further analyze my customer data by applying filters.   For example I would like to understand the specific interests of my customers from Germany.   The summary section and interest tag cloud  are quickly rebuilt, and the statistics are delivered on the fly.  I can also create a target group from the Profile Dashboard. For example,  I only want to have contacts in my target group who are interested in  the Gallo D’Oro brand Arabica Beans  and Fair Trade. Here, I can see the number of contacts that are selected. I click 'Create Target Group' and provide a name for it. So, as you can see the Profile Dashboard app provides  customers insights at an aggregated level based on criteria I specify.   So far, I gained insights into my entire contact base. If I’d like to take a closer look at an individual contact, I can open the Contact application.   The contact app allows me to see how customers interact with my business. This 360-degree view is constantly updated with new interactions and real-time scoring.  Let’s, for example, look at the Profile of John Smith.  The Interactions tab provides an overview of all  interactions and interests, as well as the  channel that John Smith used to interact with my company.  Here, I can see the interests’ tag cloud for John. He is highly interested in coffee whole beans and arabica beans.  In this section I can see John Smith’s timeline across channels.  I see that he received the newsletter from our last product launch campaign. This section provides an overview over  different interaction channels including web, commerce, and others. I can see that in the last three months there are nine interactions that occurred in the Commmerce channel. and 12 interactions through the email channel.  When I filter for the Commerce channel, I can see that John recently wrote a product review.   This filtering is applied to the entire interaction timeline so I now only see interactions that John has made through this channel.  Let’s take a further look at John’s interactions in the commerce channel by going to the Commerce tab.  I can see that John’s browsing favorites are a  special chocolate and two different types of whole beans. In the Origin Data tab, I can see all different  data sources contributing to build John Smith’s 360-degree profile.   Each tile around the Best Record in the center represents an origin. Here, I can see his interactions with my sales people but this could also be my web shop or a social media channel.   All those data sources contribute to build up his profile.   The individual origins are weighted differently to reflect the reliability of the origins.  Permission Marketing provides an overview of  permission and subscription data over various communication media. I can see John Smith opted-in for marketing  communication over email and Facebook but opted-out from Google Ads.  The Leads tab gives me an overview of all lead information on John Smith. In the timeline I see how long John stayed in a  certain lead stage. There are also special lead scores available.   In the Sales Pipeline I see in which system John was converted to a lead.  Since he is a sales-driven lead, he was converted to a lead in SAP Sales Cloud.   He is also part of two lead nurture streams.  I see that he is already in the final stage in both streams.   Another useful feature is that I can rank  and classify customers to their specific needs and purposes by using scores.   In the scores tab, I can see that John has  a very high email affinity and a weak positive sentiment score.  As you saw in the demo Scoring is another key capability.  which enables you to make predictions  about future actions and contact decisions.  In SAP Marketing Cloud you can use predictive, as well as heuristic scores. Predictive scores are calculated based on predictive models and show, for example how high the buying propensity of a contact is. Heuristic scores are based on manually   defined scoring rules  to find, for instance, the best email sending time for each of your customers. Apart from a rich set of prebuilt scores  SAP Marketing Cloud allows you to set up your own scoring rules or predictive models  to score both customers' profiles and underlying interactions. This helps you to rank and classify customers to your specific needs and purposes.  Based on condensed behavior data  such as Total Purchases in the past  or frequency of customer‘s web shop visits.  In summary, this variety set of statistical methods  and machine learning techniques in SAP Marketing Cloud enables you to detect patterns and trends in historical data and then use derived information  to predict customer behaviour and build up more specific target groups. Let's continue our system demo with a look at the Customer Journey Insight application. If I’d like to find the most common paths  customers traveled before they reach a specific event, such as a product purchase  or an abandoned shopping cart I can open the Customer Journey Insight application. In this example I can see all the customer journeys that customers took before they abandon a  shopping cart, across different combinations and sequences of channels. In the filter bar, I can set various parameters. For example I can specify the date range and the number of touchpoints of the customer journey.  I can also select different target groups.  In this example, I'll reduce the number of touchpoints per journey to four and the percentage of top journeys to 60. Thanks to the width of the channel I can identify the channels with the greatest impact. If I’d like to focus only on the most popular journeys, I can highlight those.  I can also create a target group for a follow-up  with those customers directly from the customer journey insight application. Let’s move on to Sentiment Engagement. Sentiment Engagement is a tool  which analyses any unstructured data including  posts from social media or other text-based  sources like emails and builds a graphical analysis of my customers’ sentiment With the help of SAP HANA Text Analysis text data can be processed automatically and helps to identify topics and sentiments. The number at top left corner indicates that there are 3,289 posts.  I would like to have a look at the posts from the last three quarters. I can set the timeframe using the time slider in the filters panel. I can also see the average sentiment, interests and tags by changing the view in the analysis panel. Let's break down the number of posts by sentiment.  This helps me to verify the effect of my campaigns which I run.  Now let’s filter for negative sentiments to drill  down to specific contacts and investigate further. I can include those customers with negative sentiment into a post group from which I can then create a target group. The customers in this target group could then, for example be addressed through a retention campaign. This wraps it up for our quick guide video on Dynamic Customer Profiling. Thank you for watching.