Cross-Channel Strategies to Prepare for the Holiday Season

While it was fairly clear that pivoting to a digital-first strategy was the way to go for the 2020 holiday season, brands face a new kind of uncertainty in 2021. This year, relying on customer insights is critical for every brand, because the greatest …

While it was fairly clear that pivoting to a digital-first strategy was the way to go for the 2020 holiday season, brands face a new kind of uncertainty in 2021. This year, relying on customer insights is critical for every brand, because the greatest challenge in 2021 is variance. The channels used by brands and consumers – whether in person or digital – could vary heavily by region, depending on vaccine policies and reopening plans. In any case, it’s imperative for brands to stay agile and start preparing early.

Three Ways to Assess Performance When Year Over Year Doesn’t Work

Our Digital Marketing Report recapping 2nd quarter performance highlighted extreme year over year trends across digital media. We all knew this was coming – after the radical shifts in ecommerce traffic during Q2 of 2020, it stood to reason that Q2 202…

Our Digital Marketing Report recapping 2nd quarter performance highlighted extreme year over year trends across digital media. We all knew this was coming – after the radical shifts in ecommerce traffic during Q2 of 2020, it stood to reason that Q2 2021 would essentially see a reversal in year over year trends.

What are the Steps of Conversion Optimization

Having trouble viewing the text? You can always read the original article here: What are the Steps of Conversion Optimization
What is the job of an optimizer? Is it just improving conversion rates? If not, what is the goal of a CRO professional and wha…

Having trouble viewing the text? You can always read the original article here: What are the Steps of Conversion Optimization

What is the job of an optimizer? Is it just improving conversion rates? If not, what is the goal of a CRO professional and what are the steps of conversion optimization? Brian Massey, the Conversion Scientist, shares the steps of conversion optimization. He is the founder of Conversion Sciences, and author of the book “Your […]

The post What are the Steps of Conversion Optimization appeared first on Conversion Sciences.

Increase Analytics Influence: Leverage Predictive Metrics!

Almost all metrics you currently use have one common thread: They are almost all backward-looking. If you want to deepen the influence of data in your organization – and your personal influence – 30% of your analytics efforts should be centered around the use of forward-looking metrics. Predictive metrics! But first, let’s take a small […]

The post Increase Analytics Influence: Leverage Predictive Metrics! appeared first on Occam’s Razor by Avinash Kaushik.

Almost all metrics you currently use have one common thread: They are almost all backward-looking.

If you want to deepen the influence of data in your organization – and your personal influence – 30% of your analytics efforts should be centered around the use of forward-looking metrics.

Predictive metrics!

But first, let's take a small step back. What is a metric?

Here’s the definition of a metric from my first book:

A metric is a number.

Simple enough.

Conversion Rate. Number of Users. Bounce Rate. All metrics.

[Note: Bounce Rate has been banished from Google Analytics 4 and replaced with a compound metric  called Engaged Sessionsthe number of sessions that lasted 10 seconds or longer, or had 1 or more conversion events or 2 or more page views.]

The three metrics above are backward-looking. They are telling us what happened in the past. You'll recognize now that that is true for almost everything you are reporting (if not everything).

But, who does not want to see the future?

Yes. I see your hand up.

The problem is that the future is hard to predict. What’s the quote… No one went broke predicting the past. :)

Why use Predictive Metrics?

As Analysts, we convert data into insights every day. Awesome. Only some of those insights get transformed into action – for any number of reasons (your influence, quality of insights, incomplete stories, etc. etc.). Sad face.

One of the most effective ways of ensuring your insights will be converted into high-impact business actions is to predict the future.

Consider this insight derived from data:

The Conversion Rate from our Email campaigns is 4.5%, 2x of Google Search.

Now consider this one:

The Conversion Rate from our Email campaign is 4.5%, 2x of Google Search.

Our analysis suggests you can move from six email campaigns per year to nine email campaigns per year.

Finally consider this one:

The Conversion Rate from our Email campaign is 4.5%, 2x of Google Search.

Our analysis suggests you can move from six email campaigns per year to nine email campaigns per year.

We predict it will lead to an additional $3 mil in incremental revenue.

The predicted metric is New Incremental Revenue. Not just that, you used sophisticated math to identify how much of the predicted Revenue will be incremental.

Which of these three scenarios ensures that your insight will be actioned?

Yep. The one with the Predictive Metric.

Becaues it is hard, really hard, to ignore your advice when you come bearing $3 mil in incremental revenue!

Starting your Predictive Metrics journey: Easy Peasy Lemon Squeezy.

In a delightfully wonderful development, every analytics tool worth its salt is adding Predictive Metrics to its arsenal. Both as a way to differentiate themselves with their own take on this capability, and to bring something incredibly valuable to businesses of all types/sizes.

In Google Analytics, an early predicted metric was: Conversion Probability.

Simply put, Conversion Probability determines a User’s likelihood to convert during the next 30 days!

I was so excited when it first came out.

Google Analtyics in this instance is analyzing all first-party data for everyone, identifying patterns of behavior that lead to conversions, now looking at everyone who did not convert, and on your behalf giving a score of 0 (no chance of conversion) to 100 (very high chance of conversion).

Phew! That’s a lot of work. :)

What’s particularly exciting is that Conversion Probability is computed for individual Users.

You can access the report easily in GA: Audience > Behavior > Conversion Probability.

google_analytics_conversion_probability_report

An obvious use of this predicted behavior is to do a remarketing campaign focusing on people who might need a nudge to convert, 7,233 in the above case.

But, there are additional uses of this data in order to identify the effectiveness of your campaigns.

For example, here is the source of traffic sorted by Average Conversion Probability

conversion_probability_report_3

In addition to understanding Conversion Rate (last column) you can now also consider how many Users arrived via that channel who are likely to convert over the next 30 days.

Perhaps more delightfully you can use this for segmentation. Example: Create a segment for Conversion Probability > 50%, apply it to your fav reports like the content ones.

There is so much more you can explore.

[TMAI Premium subscribers, to ensure you are knocking it out of the park, be sure to review the A, B, O clusters of actionable recommendations in #238: The OG of Analytics – Segmentation! If you can’t find it, just emial me.]

Bonus Tip: I cannot recommend enough that you get access to the Google Merchandise Store Google Analytics account. It is a fully working, well-implemented real GA data for an actual business. Access is free. So great for learning. The screenshot above is from that account.

Threee Awesome New Predictive Metrics!

With everything turning over for the exciting world of Google Analytics 4 you get a bit more to add to your predictive metrics arsenal.

Conversion probability is being EOLed with GA 4, but worry not as you get a like-type replacement: Purchase Probability

The probability that a user who was active in the last 28 days will log a specific conversion event within the next 7 days.

Currently, purchase/ecommerce_purchase and  in_app_purchase events are supported.

You can do all of the same things as we discussed above for Conversion probability.

To help you get closer to your Finance team – you really need to be BFFs with them! – you also get a predictive metric that they will love: Revenue Prediction

The revenue expected from all purchase conversions within the next 28 days from a user who was active in the last 28 days.

You can let your imagination roam wild as to what you can do with this power.

Might I suggest you start by looking at this prediction and then brainstorm with your Marketing team how you can overcome the shortfall in revenue! Not just using Paid strategies, but Earned and Owned as well.

Obviously in the rare case the Revenue Prediction is higher than target, you all can cash in your vacation days and visit Cancun. (Wait. Skip Cancun. That brand’s tainted. :)

There’s one more predicted metric that I’ve always been excited about: Churn Probability.

The probability that a user who was active on your app or site within the last 7 days will not be active within the next 7 days.

What’s that quote? It costs 5000x more to acquire a new User than to retain the one you already have? I might be exaggerating a tad bit.

For mobile app/game developers in particular (or for content sites, or any entity for whom recency/frequency is a do or die proposition). Churn is a constant obsession and now you can proactively get churn probability. Make it a core part of your analytical strategy to understand Behavior, Sources, Users, who are more/less likely to churn and action the insights.

GA 4 does not simply hand you these metrics willy-nilly. The algorithms require  a certain number of Users, Conversions etc., in order to ensure they are doing sound computations on your behalf.

These three predictive metrics illustrate the power that forward-looking computations hold for you. There are no limits to how far you can take these approaches to help your company not only look backwards (you’ll be stuck with this 70% of the time) but also take a peek into the future (aim to spend 30% of your time here).

And please consider segmenting Purchase Probability, Revenue Probability and Churn Probability!

Bonus Tip: If you would like to migrate to the free version of Google Analytics 4 to take advantage of the above delicious predictive metrics, here’s a helpful article.

Predictive Metrics Nirvana – An Example.

For a Marketing Analyst, few things come close to nirvana in terms of forward-looking predictions from sophisticated analysis than to help set the entire budget for the year including allocation of that budget across channels based on diminishing returns curves and future opportunity and predict: Sales, Cost Per Sale, and Brand Lift.

Here’s how that looks from our team’s analytics practice…

predicted_budget_channel_allocation_sales

Obviously, all these cells have numbers in them. You’ll understand that sharing them with you would be a career-limiting move on my part. :)

I can say that there are thirteen different element sets that go into this analysis (product launches, competitor behavior, past analysis of effectiveness and efficiency, underlying marketing media plan, upcoming industry changes, and a lot, lot, lot, of data).

Supercool – aka superhard – elements include being able to tie Brand Marketing to short, medium, long-term Sales.

Forward-looking allocations are based on simulations that can take all of the above, to answer low, medium, high-risk plans – from which our senior leader gets to choose the one she believes aligns with her strategic vision.

[Note: Strictly speaking what we are doing above is closer to Predictive Modeling, even though we have a bunch of Predictive Metrics. Potato – Potahto.]

I share our work as a way to invite your feedback on what we can do better and in the hope that if you are starting your Predicted Metrics practice, that it might serve as a north star.

From experience, I can tell you that if you ever felt you as an Analyst don’t have influence, that your organization ignores data, then there is nothing like Predicted Metrics to deepen your influence and impact on the business.

When people use faith to decide future strategy, the one thing they are missing is any semblance of what impact their faith-based strategy will have. The last three rows above are how you stand out.

BOOM!

The Danger in Predicting the Future.

You are going to be wrong.

A lot, initially. Then less over time as you get better and better and predicting the future.

(Machine Learning comes in handy there as it can ingest so much more complexity and spit out scenarios we simply can’t imagine.)

But, you will never be exactly right. The world is complicated.

This does not scare me for two reasons, I urge you to consider them:

1. Very few companies drove straight looking out of the rear view mirror. But, that is exactly what you spend time trying to do every single day.

2. Who is righter than you? The modern corporation mostly runs of faith. You are going to use data, usually a boat-load of it. It is usually far better than faith. And, when you are wrong, you can factually go back and update your models (faith usually is not open to being upgraded).

So. Don’t be scared.

Every time you are wrong, it is an opportunity to learn and be more right in the future – even if perfection will always be out of reach.

Bottom Line.

My hypothesis is that you are not spending a lot of time on predictive metrics and predictive modeling. Change this.

It is a great way to contribute materially to your company. It is a great way to invest in your personal learning and growth. It is a fantastic way to ensure your career is future-proof.

Live in the future – at least some of the time – as an Analyst/Marketer.

I’ll see you there. :)

As always, it is your turn now.

Please share your critique, reflections, tips and your lessons from projects that shift your company from only backwards looking metrics to foward looking metrics that predict the future.

The post Increase Analytics Influence: Leverage Predictive Metrics! appeared first on Occam's Razor by Avinash Kaushik.

Utilizing Merkle’s Loyalty Accelerator to Transform Brand Loyalty Programs

mmediate, authentic, and personalized interactions across channels. Our 2021 Loyalty Barometer Report found that:

81% of consumers want a relationship with a brand
64% of consumers want to receive personalized offers based on their past purchases

mmediate, authentic, and personalized interactions across channels. Our 2021 Loyalty Barometer Report found that:

  • 81% of consumers want a relationship with a brand
  • 64% of consumers want to receive personalized offers based on their past purchases
  • 58% of consumers said surprise offers and gifts are the most important way a brand can interact with them
  • Privacy concerns are increasing, but 54% of consumers still say they are comfortable letting brands use purchase history and reward status to make the rewards experience more relevant for them
  • 45% of consumers want to feel like the brand appreciates their business

Delivering on these experiences allow brands to build emotional connections that engender loyalty over time. However, creating these types of experiences requires brands to rethink their loyalty strategy, approach loyalty as a key part of CX, bring stronger focus to identity, and create more and different brand-customer interaction touchpoints.

Many brands are recognizing these needs and investing in loyalty with great results. Last year, Harvard Business Review’s The Loyalty Economy report found that loyalty leaders grow revenues roughly 2.5x as fast as their industry peers and deliver 2-5x the shareholder returns over the next 10 years. However, some brands still struggle with this transformation because of challenges like

Merkle’s Loyalty Accelerator for Adobe Experience Platform (AEP) aims to remove these brand challenges and help deliver the experiences customers are looking for with a standardized data schema focused on real-time awareness and a comprehensive view of the customer.

The Loyalty Accelerator adds a loyalty program member profile and event data from the Merkle LoyaltyPlus™ platform to AEP's Real Time Customer Profile to drive real-time, bi-directional activation through coordinated cross-channel customer experiences based on a data-driven understanding of customer behavior and needs. With it, data collected from consumers during their brand interactions –registration, engagement, profile enrichment, transactional events, offer redemption, etc. – is consolidated alongside data from CRM, point-of-sale, ecommerce, media, and other sources in a unified profile. That holistic and up-to-date identity, in turn, drives better segmentation, journey building, personalization, look-alike modeling, targeting, and conversion. For example, consider a loyalty program offer. Today, many brands use “one size fits all” promotional offers, which are easy to deploy but lack personal relevance for members, so they don’t further the relationship.

Our Loyalty Accelerator combines what we know about the loyalty member – their purchases, preferences, tier and status, and history in the program – with other data points from the AEP Real Time Customer Profile like web, CRM, and customer service activity and propensity information to determine the most relevant and valuable offer for that member right now. The member receives an offer that builds the relationship, relevance, and perhaps even some surprise and delight, and is easy to redeem across channels. The Loyalty Accelerator also tracks redemption and results, which are important data to feed the unified profile and shape future offer strategy and decisioning.

Through the Loyalty Accelerator, brands that leverage both Adobe Experience Platform and Merkle LoyaltyPlus™ can now take advantage of these key benefits:

  • Simplified martech stack: A rich, unified customer profile with a single ID across Adobe Experience Cloud enriched with loyalty data from Merkle, alongside customer experience management and workflow tools, all in one place. The Accelerator removes barriers and silos that can otherwise hamper loyalty growth and maximizes brand investment in both Adobe and LoyaltyPlus™ platforms.
  • Data-driven decisioning: Customer profiles can be queried in real time during any interaction to inform a holistic customer experience strategy that helps brands win, keep, and grow their best customers through relevant, compelling messaging and offers.
  • Unified orchestration: Customer experience management is coordinated across touchpoints with cross-channel member experience, targeting, segmentation, and personalization, planned and activated inside Adobe Experience Cloud and LoyaltyPlus™.
  • Better customer engagement: The combination of a unified profile and more robust data enables enhanced, catered customer experiences where loyalty serves as always-on fuel for data and identity, and loyalty marketing activations provide moments of value across the customer’s journey. All through a secure, compliant integration with governance and privacy by design.

Ultimately, the combined power of Adobe and Merkle platforms that our Loyalty Accelerator brings can help brands transform their approach from a loyalty program to an integrated loyalty experience management strategy and create valuable, engaging touchpoints for customers along the journey.

Key Media Insights from Merkle’s 2021 Q2 Digital Marketing Report

In Q2 2021, consumers shifted their digital purchasing behavior as pandemic limitations relaxed in the US. However, manufacturing and shipping challenges impacting supply and delivery pipelines nationally, which was highlighted in mid-late Q2, as Amazo…

In Q2 2021, consumers shifted their digital purchasing behavior as pandemic limitations relaxed in the US. However, manufacturing and shipping challenges impacting supply and delivery pipelines nationally, which was highlighted in mid-late Q2, as Amazon’s Prime Day took place in June. In a rebounding economy, travel and B2B advertisers made their long-awaited growth acceleration.

Let’s dive into some of the key insights from Q2:

Facebook spending saw massive growth for Q2 (+68% Y/Y) as the US began to emerge from the COVID-19 pandemic that had begun exactly a year prior.

Q2 was a pivotal quarter in both 2020 and 2021, aligning with the onset of and emergence from the COVID-19 pandemic. Q2 2020 saw the lowest Y/Y increase in spend of all quarters (+4%) since 2019, magnifying the Q2 2021 Y/Y increase (+68%). Advertisers ramped up social efforts following an unprecedented year of store closures and business constraints, driving increased competition and higher CPM within Facebook this past quarter.

Spend growth for Amazon Sponsored Product ads increased 28% YoY, due to CPC hikes (+55%) and Prime Day in June. For the first quarter in recent years, clicks growth saw a deceleration, dropping 18%. Sales were up 8%, showing modest growth but not keeping pace with spend trends. 

Driven primarily by large Q/Q bumps in spend share for Pinterest (2x) and Snapchat (5x), the smaller social platforms are increasing their presence in the media mix for brands also running Facebook and Instagram. Moving into Q2 2021, TikTok made its debut with a 0.5% share in social spend, edging out LinkedIn as a top 3 smaller social platform (down 97% in spend share Q/Q).

Want to learn more? Check out Merkle’s 2021 Q2 Digital Marketing Report here.

I Am Merkle, Vol. 12

I Am Merkle is a series of interviews that showcase the individuals who make Merkle a unique and diverse place to work. This month, learn more about our featured employees from the UK DEI team, Dinah Musisi and Ryan Skeet.

1. Tell us about yourself; w…

I Am Merkle is a series of interviews that showcase the individuals who make Merkle a unique and diverse place to work. This month, learn more about our featured employees from the UK DEI team, Dinah Musisi and Ryan Skeet.

1. Tell us about yourself; where did you grow up? Where do you live now?

Dinah: I grew up in South London. While I have travelled and lived in other parts of the UK, I have always gravitated back to South London. This part of London has always been close to my heart because of the rich culture and diversity of the area. I was born in London, but my parents came over to the UK forty-five years ago from Uganda to escape Idi Amin; they were both in hiding with my older sister for six months before they left the country. My dad is Ugandan / Kenyan, and mum is Ugandan/ Pakistani which was quite unique when they were growing up. This helped shape my unique upbringing. I can still make great pilau rice, the best curries, and questionable samosas. I have three nephews and one niece who keep me on my toes, entertain me, and give some of the best cuddles around!

Ryan: I was born in a small town called Redditch, near Birmingham; which (contrary to popular opinion, perhaps – a lot of people think Manchester) is the UK’s second city! I also studied there; so, apart from a year living in Tokyo, it’s the only place I’d lived until I moved to London to join Merkle.

2. What drew you to your current career?

Dinah: When I finished school, I initially thought I wanted to be a fine art painter and I was accepted into one of the best art colleges in London. I was obsessed with the impressionists, Frieda Khalo and Georgia O’Keefe. I was never sure what I wanted to do, so I decided to postpone starting college to earn my art degree and, instead, travelled the UK as a salesperson. I was lucky enough to help set up offices across the UK. When I came back to London, I decided not to start working towards my art degree. I was too scared of being a struggling artist. So, I decided to study English and American literature while working. I have always enjoyed creating and having constant change, so being in facilities you get to experience variety. The offices help to build culture, and while we are shifting to a “new normal”, being able to create the spaces people enjoy and thrive in has always been my passion.

Ryan: I actually sort of “fell into” PPC. You’ve heard the Avenue Q song “What do you Do with a B.A. in English?” (if not, check it out – a bit crude but funny). I took a meeting with a career advisor, who walked me through three questions: What will make you happy in life? What level of income do you need to achieve those things? What job can you do that provides that income and matches your skillset? A few graduate job board searches later, and I’d applied for (then) Periscopix – and the rest is history!

3a. What inspired you to become a part of DEI? 

Dinah: 

The past 18 months has been a rollercoaster and I have learned a lot about myself. I have always been aware of my wonderful heritage but never really shared it with people; I tended to shy away. The past year has sparked conversations about race and identity. I found myself having open conversations with friends and colleagues about their lived experiences and my own lived experiences, which created camaraderie and real appreciation about their unique identities. People are beginning to become more confident when it comes to addressing ethnicity, and I think it is important to celebrate, support and amplify the unique cultures and ethnicities the people we work with have. 

Ryan: Merkle is the first company where I’ve felt safe being open about certain aspects of my identity (namely that I’m queer and a huge nerd). I’ve found that, by being open and sharing these aspects of myself, I’m inspiring others to be more authentic at work too. There are some ways in which equality has taken positive steps over recent years, but other ways in which inclusion has really been halted or even taken reverse steps (restrictions on access to life affirming healthcare for trans people; anti LGBT zones; racially motivated hate on social media) and we have a responsibility to our colleagues and the wider community to ensure that Merkle is a safe-haven against this sort of hate.

3b. What part of your new position are you most excited about? 

Dinah: As I have grown over the past few months, I want to help ethnically diverse colleagues make a change by building confidence while being able to support and amplify each other. I’m most excited to help build and shape the Ethnicity pillar. I enjoy being in a constant state of movement and am looking forward to driving the goals we have to create a truly inclusive culture. I’m looking forward to bringing people on the journey and seeing them (and the pillar) flourish.

Ryan: Having been able to contribute so strongly to achieving progress in LGBTQ+ endeavours at the company, I’m excited to be taking on a wider remit in pulling together all DEI efforts for Merkle in the UK. Intersectionality is a fundamental part of existence which cannot be ignored. My experience growing up as a queer person of colour, has been significantly different than the experiences of my white colleagues. These intersections need to be recognized in the nuances of what we do here.

4. What is your biggest accomplishment?

Dinah: Paying for my education while studying. I worked during college so that I could pay for my tuition.

Ryan: Within my first year at Merkle, I had made a name for myself as someone unafraid to ask the tough questions. Periscopix had no parental leave policy and when it was being discussed and introduced, the language used was very focused on maternity. I raised the issue of adoption, shared leave, and same-sex parents. As a result, the policies created were more inclusive from the outset.

5. To date, what has been your biggest learning or teaching moment?

Dinah: I haven’t had one singular learning or teaching moment as they can all creep up on you when not expected. When it comes to the past two years, I think, personally, it has been about being able to believe in myself and my voice. I have been fortunate enough to be around people who have helped to build and support me and my growth. I hope that I will be able to do that for others too.

Ryan: I volunteer at an annual camping event for Japanese Culture enthusiasts (read: otaku festival), and one year I was supervising an activity where a bit of a scuffle broke out between two people. Looking at them, I made an assumption and called out “Ladies, ladies, please let’s calm down!”. The two people’s faces immediately fell and, as it transpired, I had misgendered them. I will never forget the impact that had on their experience at the event and I have always fought for proper gender recognition since. It taught me that, while mistakes happen, it’s our responsibility to treat others with respect.

6. What is a moment in your life that defined or shaped who you are today?

Dinah: Personally, it was when I realised my parents are people. Growing up in London, I didn’t realise the privileges I had until I was older. My parents sacrificed a lot for my siblings and me. They migrated to another country, put up with my siblings and me (we were terrors when we were growing up), worked full-time jobs and built a life away from what they knew.  To me, they are the real powerhouses who shaped who I have become.

Ryan: As anyone who has spent even five minutes talking to me will be able to tell you, I lived in Japan working as an ESL teacher before coming to Merkle. After having lived quite inauthentically at university before that, and fearing negative treatment in a society which is known to have quite unwelcoming attitudes to LGBTQ+ people, I hid my orientation. The isolation and hard work of keeping such a secret weighed on me the whole time, and I came to the conclusion that I could only work in an environment where I could be myself after that experience.

7. What inspires you about your workplace culture?

Dinah: When I started with Periscopix, and now Merkle, it was the people and atmosphere that inspired me. You spend most of your time with your colleagues, so it is essential you enjoy the people you are around.

Ryan: One word: collaboration. In a lot of companies, competition is key, and people jealously guard their work to maintain an edge. This just isn’t the case at Merkle where we succeed together through sharing knowledge and ideas.  

8. If you currently weren’t doing what you do today professional, what would you be doing? (dream job)

Dinah: A travel blogger so I can see the world. I enjoy exploring new places and can often be found in some remote location relaxing.

Ryan: Probably a professional travel reporter. Visiting beautiful places, seeing amazing sights, and eating wonderful food – and getting paid to sass it all?! Ideal 😉

9. What was the first concert you went to?

Dinah: I can’t remember the concert, but my first single was “Push-it” by Salt-N-Pepa

Ryan: I was around 15 when I first went to see Yellowcard in a nice cosy, intimate venue. I began a 10-year love affair with live music after that, which only ended when time and money became too scarce.

10. Rapid fire

a. Favorite food

Dinah: Pork Tortas - if you know, you know!

Ryan: A dish popular in Tokyo called abura soba (oil noodles). It’s FULL of flavour but mega high in calories!

b. Favorite TV show/movie

Dinah: Anthony Bourdain: Parts Unknown – food and travel are my favourite things!

Ryan: Would have to be Buffy the Vampire Slayer. That’s a cult classic!

c. Favorite hobby/activity

Dinah: Backgammon

Ryan: I probably sink at least six hours a week into Dungeons and Dragons between the two games I run for different groups and the three games I play in (on and off).

d. Favorite book

Dinah: Lord of the Rings

Ryan: Torn between “His Dark Materials” and “The Wheel of Time” (both are series, I realise, not individual books). If I had to choose just one, it’d be New Spring.

e. Guilty pleasure

Dinah: 90’s R&B / Hip-hop

Ryan: I don’t believe in guilty pleasures. Being a nerd is about unapologetically and passionately enjoying the things you love.

f. Best advice or mantra you live by (in your own words)

Dinah:  If— BY RUDYARD KIPLING

If you can keep your head when all about you  

    Are losing theirs and blaming it on you,  

If you can trust yourself when all men doubt you,

    But make allowance for their doubting too;  

If you can wait and not be tired by waiting,

    Or being lied about, don’t deal in lies,

Or being hated, don’t give way to hating,

    And yet don’t look too good, nor talk too wise:

Ryan: Everyone you will ever meet knows something that you don’t. Go into any new encounter expecting to learn and you won’t be disappointed.

How the Travel Industry Can Use Customer Journey Analytics for COVID Recovery

There’s no question that the travel industry was one of the hardest hit industries from COVID-19 during the past 14 months. Now, some of the industry is starting to bounce back and regain the course that was leveled last year. As the industry begins th…

There’s no question that the travel industry was one of the hardest hit industries from COVID-19 during the past 14 months. Now, some of the industry is starting to bounce back and regain the course that was leveled last year. As the industry begins the legwork of recovery, analyzing the customer journey can play a key part in understanding how customers are engaging with the brand and buying.

Customer journey analytics is the approach to building informed customer experiences to maximize the impact of marketing efforts and minimize waste in marketing dollars. As it evolves, it requires some new skills and approaches to get it right. It starts with informing how we understand the customer, then it influences how we design the experiences, informs how we operationalize the changes, and helps to shape individual experiences in real time. At its best, customer journey analytics ensures a systematic means of evaluating and monitoring outcomes and continuously improving the process.

Segmentation is Key

Not every customer is the same or wants to engage with your brand the same way. Therefore, one of the biggest focus areas of how to manage customer journey analysis and planning for the travel industry is around segmentation.  Everything needs to start with the customer segmentation in mind and tie back to that, especially during the COVID-19 rebound effort. The segmentation type can be selected based upon comfort level as well as desired speed to market.

Common Segmentation Approaches:

  • Statistical clustering to build mutually exclusive personas – An ideal approach that can inform media and creative strategy but takes longer to develop
  • RFM (recency, frequency, monetary value) rules-based – Higher speed to market but less accurate/holistic

The value component in segmentation greatly aligns with loyalty and how much someone spends with the travel company. Communication plans need to be very tightly informed by this information.

At a high level, a basic customer journey segmentation could look like this:

High value customer

This customer is in the ideal spot where we want all customers to land. These customers are brand advocates, are all in on your loyalty program, and they frequently support your brand. This segment should be used as the lynchpin to follow for other groups. Understanding what makes this segment valuable to your brand (beyond potentially having higher disposable income) and how they engage with your marketing touchpoints is crucial and can be teased out via the customer journey analytics process.

Medium value customer

Insert marketing touchpoints that are relevant to the high value segment to help replicate the high value segment success. You may find that the medium value group responds to a certain channel over another to bring more conversations. Double down on what is successful to make this group successful. Do you need to give incentives for lower groups? They could command a lower income and could benefit from deals or offers, or a more specific type of offer that helps them convert. Analyzing existing customers will inform how to build lookalike audiences to talk to prospects in a similar manner. Not every customer is the same, and because of that, marketers need to think like that today, especially in paid media activation.

Low value customer

These customers are low spenders and may only purchase when you have deals. However, this group is also important in your customer journey analytics as they can be studied to find targeting attributes or touchpoints to omit in your marketing efforts. It is important to understand what motivates this group and understand why they don’t make more purchases. This information can be used to avoid wasting ad dollars on similar customers.

Another important segmentation to consider is prospective customer vs. current customers. To do this, take all your data points, lay them out, and see how conversions are driven from your prospects and your current customers. What is drawing in new customers, and what are you doing that is keeping them coming back? Extract insights to find what makes high value customers, then try to replicate further (extract specifics on what makes them valuable). As an example, think about a frequent flyer loyalty card. If you don’t have a loyalty program, these analyses will be made from scratch. The focus should be on driving profitable conversions, so conversions shouldn’t be looked at as a whole but instead broken out using your segmentation framework.

Most travel organizations have a loyalty component. Therefore, loyalty needs to be instrumental to your strategy in this process. From here, depending on the company, it may make sense to create subgroups to hone into specific audiences based on your goals. Customer journey analytics analyzes what happens today and where to be to bridge the gap, so think about the segments that make up your most valued customers.

Common Pitfalls of Customer Journey Analytics

  • The journey analysis needs to be grounded in data from start to finish. It’s a science and an art but goes beyond simple gut feelings
  • What you want customers to do is one thing and what they actually do is another
  • Misconceptions of what customer journey mapping actually is. Start with data analysis and evolve it into a strategy. Start with the facts, layer in a measurement framework to understand how people are moving from step to step
  • As you’re developing your creative/messaging strategy from the customer analysis, avoid tone deaf messaging, personalize, especially for your known customers. People expect personalized experiences and if you don’t do it, they can become a detractor for your brand 

Want to learn more? Check out our handbook, The Ultimate Guide to Customer Journey Analytics here.