Skip navigation

Hello All, the new Eloqua Insight (OBIEE) is coming and Classic Insight will be deprecated next year (Classic Insight Sunsetting (Sept 2018)). Unfortunately, there are a few features that were obvious to do in Classic that aren't so obvious in the new Insight. One of them being how to create a dynamic date filter (i.e last 1 day, last 7 days, last month, etc). In the new Insight, the options look to be for static ranges only. This is a problem if you have scheduled email reports that you want to see only recent data. An example we have is to see all the emails sent in the last week and the metrics around them that we receive on a weekly basis. We have found a way to use dynamic filters using SQL. Please see how we did it below.

 

1.  Find the report you want to add the filter to and hit 'Edit'

 

2. Click on the add filter icon

 

3. Select the date field you want to be dynamic. If the field isn't immediately there, click on the 'More Columns' option at the bottom

 

4. Set the operater to 'is greater than or equal to', select any date for the Value, and then check 'Convert this filter to SQL'

 

5. Remove everything after the '>=' symbols

 

6. In this scenario, we will be getting everything within the last 1 day. Replace what you deleted above with this code (not including quotes): "TIMESTAMPADD(SQL_TSI_DAY, -1, CURRENT_DATE)". The "-1" represents the amount of days and you can change the number depending on how many days you want to look back.

7. Click 'OK' and you now have a dynamic date filter.

 

Please note that this is something that we found ourselves and may not be officially supported by Eloqua. Please do not contact support with questions on how to do this. Happy to to field any questions you may have on this through the thread. Thanks!

AI is all over the news these days. It’s hard to know how to make it work for your marketing team. This post outlines some practical tips in using the Oracle Marketing Cloud and AppCloud offerings like Motiva AI to bring new adaptive intelligence capabilities into the way you design, execute, and improve your marketing programs.

 

When you get beyond the term “Artificial Intelligence”, you’re really just talking about software that learns to do things. There are lots of opportunities where you can get started with AI today that will have a measurable impact on your marketing. Here are five tips for how to go about it.

 

Tip #1: Start simple

Don’t try to take too much on with AI out of the gate. Start small, show some results, and then build on your success. Begin with simple proof of concept use cases that you can measure easily. A good candidate here is message testing in a single campaign – but going beyond simple A/B type testing. You can use a tool like our own Motiva AI to test and automatically find winning messages that lead directly to campaign response improvement. Profit!

 

Tip#2: Match the right task with the right tool

There are some tasks that machines tend to do better than people - and machine learning applications will get better at it over time. Here are some great candidates:

  • Audience segmentation and definition
  • Message testing and optimization
  • Personalization
  • Send time optimization
  • Data cleaning
  • Advanced analytics

 

Example: A large national healthcare company recently decided to focus on message testing and optimization, and used the Motiva AI Cloud for Eloqua on a patient-facing audience and saw a 200% difference in click-through rate by simply trying lots of message variations in the population. Motiva adapted to the audience preferences it observed, which allowed the campaign to adapt organically. A simple place to start, with big impact.

 

Tip #3: Look for “10x” opportunities

Ask yourself: where could we make the biggest impact in terms of customer response or labor savings? More often than not, machine learning can at least help the human marketers improve decision-making; in some cases, you can just outsource the entire workflow to intelligent helpers. Campaigns that most directly touch revenue or direct conversions are great places to improve pipeline dynamics.  Combine that with labor savings from automation. 

 

Tip #4: Measure and improve

It’s vital to think about what your definition of success is for a given use of machine learning and how you’ll measure progress towards your goals.

 

  • Will it be in terms of time saved for your marketers? Then track their time – develop a baseline for the workflow you’re interested in and the difference over time.
  • Will it be in terms of campaign performance? Again, make sure you’re collecting the data and reporting for the story you want to tell.
  • Will it be in terms of effects downstream in the sales process?  Ensure you can track your treatment effects all the way through your pipeline.

 

It’s not difficult, but you do have to do it. It’s just good modern marketing practice.

 

Tip #5: Remember it’s about your audience, not just the tech

Your number one concern should be how to develop that communication channel with your end audiences. Technology can be super useful here, but not all technology and not all the time. In terms of AI-driven tools, ask yourself:

  • Does this help me learn more about my customers and their needs?
  • Does it help me serve my customers better?
  • Does it strengthen the customer experience?

 

Make a connection between the tools you’re using and how they ultimately lead to positive customer impact.

 

The adaptive future

These tips are a place to begin to think about how to bring machine intelligence into your marketing. We are just seeing the start of a marketing revolution with machine intelligence combined with human intelligence.

 

For more information on Motiva AI, check out our free pilot in the Oracle AppCloud.

Filter Blog

By date: By tag: