PEGA Simulation - Test and Learn Approach to Maximize the Marketing KPIs

What is ‘test and learn’ marketing?

Test and learn marketing is a data-driven approach to constantly optimizing Strategies and to improve the KPIs performance of recommendations made from PEGA Decisioning Simulation capability through a series of ongoing tests. It allows organizations to convert insights into hypotheses and then test those theories to prove their value. Primarily to improve the take rate of recommendations made from PEGA OR it could be improving the revenue AND/OR margin for an Organization. It also could be a two different variant of the Treatment for the same action to the same channel. Eg. Having two variants of the Email treatments for the same Action. This is a perfect example of test and learn marketing.

Test: Taking the guesswork out of marketing

Test and learn principles remove this speculation by building a data-driven system that proves the success and failure of individual marketing strategies. Instead of relying on correlative insights, we can run the PEGA Simulation to attribute meaningful KPIs to each change, measure performance and test variations to determine which strategy is most effective.

Learn: Turn insights into better marketing decisions

The learn aspect can be as simple as finding out which hypotheses are correct and prioritizing them in order of value (which meets the Organisation KPIs objective already set). We can also learn from previous experiments (and their data) to create new hypotheses or determine which testing opportunities meeting the marketing KPIs.

We could also leverage an existing PEGA Decisioning Machine learning AI capabilities like Adaptive Modelling, Predictive Modelling to experiment to spot opportunities for testing, makes recommendations based on your results and predicts the outcome/value.

A good test and learn marketing principles has two main objectives:

1. Increase conversion rates through testing variations.

2. Learn from previous tests and apply findings to future marketing decisions.

We run a series of tests to determine the best outcome for specific scenarios and we collect all of this data to spot patterns and inform smarter marketing decisions.

By applying a test and learn model to all of our marketing campaigns, we can improve every aspect of brand performance with data-driven insights. The more tests you run and the more data we collect, the more reliable these insights become and the more robust our marketing decisions will be.

Some of the example of Goal for Test-and-Learn approach

• Measure the Impact of Decisioning Framework values (Real Time Controls) changes and to align Organizational KPIs

• Test the effectiveness of different treatments for the same Action for the same Channel Eg: Keep different Email Treatment (Title and/or content) for Control and Test to measure the impact

• Determine which Treatment Content generate the highest engagement.

• Test the potential value of a new Channel.

• Calculate the lifetime customer value of leads based on acquisition channel and their position along your marketing funnel.

• Identify negative friction that’s preventing leads from converting into customers.

• Optimize marketing funnel to reduce dropouts and maximize conversions.

• Optimize the customer experience to maximize repeat purchases and lifetime customer value.

A test and learn model can be applied to any marketing objective and campaign type where we want to maximize performance and collect insights to inform better marketing decisions in the future.

How to apply a test and learn model in PEGA Decisioning & Marketing

Some quick overview of the key steps to take in test and learn model are:

1. Define goal and KPIs: It’s crucial that Organisation should have a specific goal in mind and understand which KPIs truly measure success. It could be higher engagement reate, higher order rate, improving revenue, margin and reducing churn etc.

2. Develop hypothesis: This is the theory that your tests will prove or disprove – to achieve the same KPI, there could be different school of thoughts. Ideas will help us to develop hypothesis.

3. Create testing criteria: To get meaningful results from tests, weneed to define strict testing criteria and remove every possible variable that might skew the desired outcome.

4. Test ideas with the highest potential first: This will have the biggest impact on performance and collect the most valuable data early on – but it also ensures that our test and learn models achieve a positive ROI as soon as possible.

5. Run your tests until statistical significance: This ensures your results are reliable enough to inform decisions while mitigating for variables outside of your control.

6. Turn insights into action: Individual results help you make specific decisions but collecting data from all of your tests helps you to make informed predictions and decisions for future campaigns – for example, which ad format is most effective for your campaign message or how much to bid to achieve your target reach.

7. Measurable success post implementation: Once right Strategy has been identified, implement the hypothesis produced results closed to KPIs and make the BI tools in place to measure the success/failure of the recent change.

8. Apply Continuous Improvement Technique: By learning from successes and failures, we continue to do what works and constantly improve upon what doesn’t

This test and learn approach can be applied to any marketing strategy and, PEGA Customer Decision Hub Simulation capability would help to achieve the possibilities in a quick turn-around time.

Happy Learning!

Nanjundan Chinnasamy

Enhance Your Personalized Messages to Customer using External Data Feeds/Public data

Mostly Organizations are using their own Customer Analytical Records (All the information about a Customer data, products, usage and Marketing data) as part of Decisioning process whether its Inbound channel Real-Time request or Proactive outbound communication to send the personalized marketing message using tools like PEGA CDH, Adobe, SAS, Unica etc.

Personalization has become a must-have for messaging because of high customer expectations. To take Marketing personalization to next level, integration of external data feeds/publicly known information about the customer as part of Decision making process is inevitable.

I would like share few use cases which can enhance personalized messages to Customer in the Communications and Banking industries.

External Data Feed#1: Integrate Official Emergency services & weather alert systems API data to PEGA Decisioning engine

Using weather alert system data & joining the same with Organizations own proprietary Customer Analytical Records will help Organizations to target the Customers affected by bad weather/ natural disaster. (Post code can be used to identify the customers impacted to send hyper personalized marketing message). External data source will help Organization to prioritize the Nurture/Service messages to the Customers over Sales message.

Corporates can also use the publicly available weather alert systems API Data & send proactive service/alerting messages. Timely, relevant and Empathetic message will help Organization to increase customer Life Time Value and NPS.

Sample use cases to use the External source data to send hyper personalized Marketing message:

When customer postcode matches with natural disaster affected postcode:

o    For Banking & Communication, Waive-off late fee & allow them to pay the bit later

o    For Communication, Make some additional data & call free offer for affected customers until the situation is restored

o    For Communication, Send proactive service outage messages & notify the team who are managing the Infrastructure/Towers about the event.

o    For Banking & Communication, Prioritize the Nurture messages over sales (send proactive service outage message with ETA to restore the service)

o    For Travel, send a message with weather information for an upcoming trip

o    For Retail, send users a list of products that they might be interested in based on the current location (if its affected by Bad weather)

External Data Feed#2: Integrate Foreign Exchange API data to PEGA Decisioning engine

For the customers who are buying the ForEx regularly OR the Customers who are setup the Standing order to other Country, proactive personalized offer when there is a significant change to the ForEx will help Customers to book the ForEx in advance.  Hyper personalized Marketing message will help Banks to increase their ForEx sales and Customers would happy with the Exchange Rate deal they received.

To talk specific to PEGA Decisioning, mostly the prioritization of the offers/Actions is combination of ADM Propensity, Context Lever, Offer Value, Business Lever etc. Managing Offer value, Business is done by the Marketing Department most of the time through Revision Management process AND/OR other well defined Rapid deployment feature. Majority of the time, the opportunity will be lost before marketing team reacting to get the Marketing lever changes validated and implemented in Production. Very few Organizations doing Rapid deployment in 2 days’ time, few are doing Revision Management deployment in 2 weeks and majority of them deploying Marketing lever changes in 3-4 weeks’ time (BAU release change release).

Integration of External source data source could also help us to override Marketing levers to specific Target Group (Customers affected by bad weather in my previous example) and also it will help us achieve automated data-driven decisions from PEGA in real-time. This will eliminate of manual lever changes to force the specific/group of propositions to the customers who are in-need.

What are the other use cases you can think about to make the hyper personalized marketing messages by integrating External data as part of Marketing Decisioning process? Please share those in comments section. 

Happy Learning,

Nanjundan Chinnasamy

Tracking effectiveness of the PEGA Marketing Campaign & real-time Decisioning response through UTM Parameters with CallToAction URL

Often enterprises having difficulties in understanding the campaign drives the maximum traffic and business to their website. Since many large scale enterprises started moving towards PEGA Centralized Decisioning Hub (Unified Marketing tool to send hyper personalized contextual, timely marketing message to the customer) to serve the marketing message, it is most important & critical for them to analyze & measure the RoI for the investments they have made.

One easy way to measure & track the effectiveness of the Marketing message sent to from PEGA for both Inbound & outbound channels is using UTM parameters to their CallToAction link.

UTM parameters come into play to analyze & measure the marketing campaign that drives maximum traffic. Organizations can plan their investment based on the historical performance in a Omni Channel Marketing environment.  

By tagging your URLs with UTMs (Urchin Tracking Module), you can understand how your visitors interact with your website/app/outbound campaign like SMS/Email.

Here’s how these UTM parameters appear at the end of your URL:

https://www.jio.com/recharge_singleclick?

planId=1008395&utm_source=NE&utm_medium=SMS&utm_campaign=Plan_expiry

Adding UTM parameters in all the CallToAction link provide extremely valuable insights from Analytics perspective to measure the effectiveness of the Offer & RoI . You can uncover a goldmine of behavioral data to help boost our sales and refine your overall marketing strategy (Offers, Channels etc). 
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What Are UTM parameters?

Here’s a succinct and super helpful definition from Kissmetrics:

“UTM parameters are simply tags that you add to a URL. When someone clicks on a URL with UTM parameters, those tags are sent back to your Google Analytics for tracking.”

As a PEGA Decisioning Consultant can plan & keep all the UTM parameters in a proposition catalog & finally build the CallToAction target link from proposition metadata.

There are five UTM parameters that you can attach to your links:

UTM source: Encapsulates the traffic source that in most of the cases is the platform on which you shared the link, for example, Google, LinkedIn, Twitter and Gmail.

UTM medium: Includes the marketing medium that is closely related to the source. For instance, if you use Google as a source, PEGACDH, Adwords etc.

UTM campaign: Underlines the campaign that you used to share the URL. You can name the campaign as you like, for example, “PlanExpiry“ for outbound campaign and “Inbound” for real time inbound call to offer recommendations from PEGA Decisioning engine.

UTM term: In most cases, this parameter is used for advertising and seizes the term you bid on for sharing your URL. For example, you might bid on the term “Drip Marketing,” and consequently, “drip marketing” will be the UTM term.

UTM content: A parameter that is used to determine the content that collected interaction when multiple elements from your ad promotion led to the click. This is especially useful if you A/B test more versions of your content.

Only UTM parameters are sufficient to measure the PEGA Decisioning performance?

NO. We can add as many custom parameters to track the marketing effectiveness (URL can have max 255 chars including params. We could add only relevant url parameters to measure the effectiveness).

Below is on the example where the CallToAction link contains the InteractionID (URL param is IxID), OfferName(URL Param O), ContentID (CONID)

https://www.pega.com/webinars/customer-engagement-series?IxID=-1055117343767813309&O=CXUnified_InsNOutsOf11Engagement_NBA500_ES1_EM181438&utm_source=LMMS&utm_medium=email&utm_campaign=Engagement_NBA&utm_content=20DE_CE_NA-NA_EM%28EM-181438%29_EM1_CI_OT_NBACDHWBSERIESREPLAYVIDEO_NA&CONID=CON-8314620

 

Why UTM Parameters Matter for PEGA Decisioning CallToAction Links?

By using UTM parameters we can gauge the types of marketing messages/offers that work and provide us with the insight needed for the ones that didn’t. Basically, there are 5 major benefits from using UTM parameters for your campaigns:

Cross-Channel Tracking: You’ve just created a dedicated landing page Or Offer message to the Market. How to measure RoI for this? What if 99% of your traffic comes from Inbound Web channel and only 1% from SMS campaign? With UTM parameters, you’ll know exactly which channel brings you long-term profits.

Improving Your Channel Campaigns: When you track the channel’s ROI and monitor the campaign’s impact, you’ll have a clearer picture of what provides you with the best outcome. Now, you’ll be able to focus on improving the channel’s impact.

A/B Testing: If you want to test two different CTAs because they both lead to the same link, you can use a UTM parameter. You can compare the engagement for both of your CTAs and determine where your target customers respond better.

Influencer Marketing: When you pay a social media influencer to market your product, you want to know if he/she really gets clicked on or it’s just a person with a fake followers count. Creating a custom URL with UTM tags can help you track their ROI efforts.

Finally,
Adding UTM parameters in all the CallToAction link provide extremely valuable insights from Analytics perspective to measure the effectiveness of the Offer & RoI . You can uncover a goldmine of behavioral data to help boost our sales and refine your overall marketing strategy (Offers, Channels etc). 

Happy Learning!
Nanjundan Chinnasamy | PEGA Lead Decisioning Architect