Filed under: #mktgcloud, Datarati, Marketing Automation | Tags: Cloud Computing
Filed under: #mktgcloud, Cloud Computing, Datarati, Software as a Service | Tags: Cloud Computing, Razorfish
Razorfish is launching a cloud computing practice to help clients maximize efficiency through the Web-based computing platform, and establish the agency as a thought leader on the emerging technology.
Smart move. I hope other digital agencies will follow suit.
Welcome Razorfish to the Marketing Cloud! #mktgcloud
Filed under: A/B Testing, CRM, Data, Datarati, Email Marketing, Forms, Lead Generation, Lead Nurturing, Lead Scoring, Marketing Automation, Optimisation, Segmentation, Technology, Testing, Web Analytics | Tags: Cloud Computing, CRM, CRM database, Customer relationship management database, Marketing Automation, Marketing Automation Database, SaaS, Salesforce.com, Software as a Service
An open letter to all Australian & New Zealand marketers:
After many years selling both Marketing Automation databases and CRM databases, services and solutions in the Australian / New Zealand marketplace, I have decided to clearly explain the difference between a Marketing Automation database and a Customer Relationship Managment or CRM database.
It seems that there is still some confusion in the local market as to how these two databases differ, how they work together and the value of integrating these two databases together.
The objective of this post is to simplify the jargon, clearly explain the key differences and empower you as a marketer to make smart data-driven decisions.
What is a Customer Relationship Management (CRM) Database:
Simply, this is a database designed to allow an organisation to do three core things:
1.) Sales teams to input, manage and track their leads that are generated by their marketing team
2.) Customer service teams to input, manage and track customer service and support quieries
3.) Marketing teams to segment customer/sales data e.g. which customers bought an iPhone in the last 6 months.
Examples of CRM databases which are stored (on-premise) i.e. database physically stored inside an organisation on their own servers are: Siebel, Oracle, Microsoft etc.
Example of a CRM database which is stored (off-premise) i.e. database physically stored outside an organisation on the vendors servers is: Salesforce http://www.salesforce.com
In today’s enviorment, most organisations across Australia & New Zealand and globally have or are in the process of moving to (off-premise) CRM databases like Salesforce.com for the costs savings and ease of use.
To access the database all a user needs is a username, password and a web-browser, as the data from the database is delivered within a users web-browser.
These types of CRM databases are referred to as any of the following: Software as a Service, SaaS, On-Demand, Cloud-based and Cloud Computing.
Ok, so as a marketer if you have a CRM database in your organisation, FANTASTIC!
It’s a start, but it only allows you to segment customer/sales data.
Today’s marketers are using multi-channels for both inbound and outbound marketing.
These channels include:
– Email (Inbound, Outbound)
– SMS (Inbound, Outbound)
– Paid Search (Inbound e.g. Google Adwords)
– Paid Display (Inbound e.g. Banner Ads)
– Landing Pages (Inbound e.g. Email, Google Adwords, Banner Ads)
– Telemarketing (Inbound, Outbound)
– Social Media (Inbound, Outbound e.g. Twitter, Facebook, Widgits)
So does your CRM database allow you to set-up, build, manage, track and optimise all of the data that is generated from the above channels?
The answer is NO! Regardless of which CRM database you are using, it does not allow you to do this, nor were they designed to.
Now, the problem that you as a marketer face is simple. When you look to execute any inbound or outbound campaigns, your data is siloed, often stored in multiple databases in multiple locations, often managed by multiple rostered agencies and/or vendors – leaving you as a marketer with little to no visibility of four of the most important things within marketing:
1.) A 360 degree view of how marketing have touched the customer or prospect i.e. which campaigns were they sent
2.) The behaviour of the customer or prospect i.e. how did they or didn’t they respond to those campaigns (conversions)
3.) What variables performed better within those campaigns i.e. creative, call to action etc
4.) Where the customer or prospect is within the customer lifecycle or buying lifecycle
Q. So how does a marketer solve this problem?
A. A Marketing Automation Database
The objective of implementing a marketing automation database is to get all the information marketing needs to acquire leads in one place. Marketers implement a marketing automation database to see all of marketing’s interactions with each prospect and customer. They also use it to keep data clean by automating the de-duplication of records within the database.
A marketing automation database is a SEPERATE database, designed to allow an organisation to do 7 core things:
1.) Lead Generation
– Objective: Make sales happy with more qualified leads.
– How: Convert website traffic into leads, automate lead development, identify when prospects are ‘sales ready’, automate sales tasks and track follow up.
2.) Lead Nurturing
– Objective: Drive revenue by nurturing raw inquiries into ‘sales ready’ leads.
– How: Nurture relationships with qualified prospects, educate leads before passing them to sales, trigger relevant responses to prospect behaviours and automate repetitive marketing tasks.
3.) Lead Scoring
– Objective: Improve sales effectiveness by passing only qualified leads to sales.
– How: Automate lead qualification processes, measure prospect interest and engagement, score leads using demographic data and behavioural data and focus sales resources on the best opportunities.
4.) Website Tracking
– Objective: Know exactly who is visiting your website and where they go.
– How: Track all prospect interactions online, identify which companies are visiting your website, monitor known and anonymous visitors and automatically alert sales reps of new prospect activity on the website
5.) Email Marketing
– Objective: Don’t just email prospects, engage them in a dialogue.
– How: Deepen realationships with triggered, multi-step campaigns, get to the inbox using the latest deliverability technology, raise and open click rates by targeting segments and track and score who opens and clicks on each email.
6.) Landing Page Optimisation
– Objective: Create, publish and test targeted landing pages.
– How: Launch new landing pages in minutes, use your own branding and subdomain, maximise conversion rates through A/B testing and capture leads with smart forms that recognise know customers and prospects.
7.) Marketing Asset Management
– Objective: Store, distribute and track content and other marketing assets.
– How: Upload and manage documents and image files, publish customised URLs for each asset, track which piece gets viewed by prospects and notify sales reps whenever key marketing assets are viewed by a customer or prospect.
Now, to get the true value out of all of the above – organisations should integrate their CRM database (which holds sales data) with their Marketing Automation database (which holds marketing data).
Why? Three simple reasons.
1.) Instead of manually exporting ‘sales ready’ leads from a marketing automation database in excel and then having your sales team manually upload the list into their CRM database, this integration automates the transfer of the marketing data from the marketing automation database into the CRM database.
2.) Sales teams are now empowered as they now have all the marketing history of how a prospect or customer has been communicated to by marketing, how they have or havn’t responded and most importantly the prospect or customers behaviour. So what that means is that the sales or telemarketing team have all of this rich actionable insight about what they prospect or customer is interested in before they make an outbound call.
3.) Closed Loop Return on Investment (ROI) reporting – by integrating your marketing automation database (marketing data) with your CRM database (sales data), you can now attribute which campaign(s) drove not only conversions but repeat purchases.
Marketing Automation databases are referred to as any of the following: Software as a Service, SaaS, On-Demand, Cloud-based and Cloud Computing. To access the database all a user needs is a username, password and a web-browser, as the data from the database is delivered within a users web-browser.
Hope this post helps to explain to all marketers across Australia & New Zealand the difference between a Marketing Automation database and a CRM database, and the power of integrating the two for full closed loop ROI analysis.
Filed under: CRM, Marketing Automation | Tags: Cloud Computing, Marketing Data, Software as a Service
I was speaking with someone during the week about hosting their marketing and campaign data ‘in the cloud’ and they looked at me funny.
Here is a simple, clear, concise explaination: http://www.youtube.com/watch?v=ae_DKNwK_ms
Filed under: CRM, Datarati, Marketing Automation | Tags: Adweek, Cannes, Cloud Computing
R/GA’s Bob Greenberg used his seminar with Hewlett-Packard CMO Michael Mendenhall to extol the wonders of cloud-based computing, and take a few shots at how advertising is structured.
Greenberg is well known, of course, for his broadsides at traditional advertising. He predicted that hosted services would revolutionise marketing, making it more important than ever for brands to earn media rather than buy it.
Filed under: Data, Research | Tags: Amazon Web Services, AWS, Cloud Computing
When will Australian data be available in the cloud on Amazon Web Services (AWS)?
Public Data Sets on AWS provides a centralised repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community, and like all AWS services, users pay only for the compute and storage they use for their own applications.
An initial list of data sets is already available, and more will be added soon.
Previously, large data sets such as the mapping of the Human Genome and the US Census data required hours or days to locate, download, customize, and analyze. Now, anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes.
Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. For example, users can produce or use prebuilt server images with tools and applications to analyze the data sets.
By hosting this important and useful data with cost-efficient services such as Amazon EC2, AWS hopes to provide researchers across a variety of disciplines and industries with tools to enable more innovation, more quickly.