Reaching retail resilience – right-sizing your tech stack and investment

The retail industry is feeling the squeeze of slowed growth and compressing margins worsened by supply chain issues and compounded by increasing inflation. Across the board, we are seeing wary consumer responses to ongoing economic uncertainty, with many pulling spending back significantly, or reallocating discretionary funds towards the increasing price of essentials.  

Challenging climates happen. Retail has weathered headwinds like this before, and we all know that preparation, efficiency, agility, and customer empathy can go a long way to developing the resilience needed to weather these storms. But how do you weave actionable resilience-building into your top-level strategy? In this blog series, I am going to outline a four-step blueprint for achieving retail resilience, and we’re going to start with your tech stack and investments.

Why it’s time to right-size your tech stack and investment

Very very few of you reading this will have had the luxury of building your stack from the ground up. The vast majority of marketing leaders inherit a tech stack, often teetering with legacy tools and point solutions, and are tasked with making it effective, efficient, and optimizing its performance and return on investment.  

The “digital transformation” that has been taking place throughout the pandemic has left teams with technical debt, rushed/poor tech decisions, and disconnects between point solutions brought on to solve distinct problems, separately. When resource constraints aren’t quite so tight, there is often a level of acceptance that your technology investment probably includes a degree of redundant or overlapping functionality. And as long as this percentage doesn’t creep too high, and complicated or fragile workflows don’t start to demand more than they deliver, then this setup can go unchecked. For example, the 2020 Gartner Marketing Technology Survey found that respondents deployed an average of 2.3 CDPs with multiple vendors, indicating that even within a very specific use case there is still a high chance of feature/functionality overlap, and also a level of dissatisfaction with standalone solutions.

When times are tough, it’s much harder to ignore overlaps and inefficiencies lurking in your toolkit, and even if you’re happy with what’s under the hood, it’s still a good time to evaluate your stack for any efficiency gains, possible reductions in spending, and alignment with your marketing goals. 

The biggest struggles we see in retail tech stacks are

1. Feature redundancy 
2. The wrong tech to support the specific outcomes needed by each retailer
3. Lack of flexibility without immense investment from tech, data, and agency/consultancy resources 

These factors all lead to overspending on tech, which isn’t just seen in the form of your contract: it’s the inefficiencies those investments introduce, how much it costs to support from both a team and time perspective, and the opportunity loss associated with the time it takes to get a campaign to market, and action the insight and data you have. 

How do you right-size the right way?

Here’s our top-bottom approach to evaluating and ultimately right-sizing your tech investment. You can do all of these or (if you feel like you have a good understanding of your existing problems, and their cost implications) you can skip straight down to #3. 

1. Take a ‘problem-first’ approach 

Identify the key problems you currently face as a marketing team. Put them in the context of the current cost of this problem (ideally in the form of annualized metrics) and the business goal the problem is impacting.

One example

Problem: poor data-to-value pipeline 

Current costs: annualized cost for agency support, tech teams, and the time to launch a data-enabled campaign

Business goal impacted: Cost savings

Another example

Problem: surfacing recommendations for the best next step in the customer journey

Current cost: Loss of incremental sales per personalized communication (you can put a target around this)

Business goal impacted: Revenue growth (or revenue maintenance in the face of a recession)

2. The $ of problem resolution

Name the potential return of solving the above problems

If you already have vendors assigned to solving these problems, partner with them to identify that potential return (if your POC/onboarding didn’t include this already, that is).

3. Understand what you have 

List all the solutions you have within your current stack and all of the resources across the business that currently support the resolution of these problems.

Determine the team, tech, or supporting consultancy’s feature capabilities that support solving those problems 

Create a comparison chart for each problem, and chosen solution, and list the features for each chosen solution

4. Evaluate your overlap 

Where you have overlap, you’ll want to pretend like you’re running an internal RFP

• Rank those overlapped features in order of importance
• How well do the chosen overlapping solutions deliver ROI against those features?
• Do you have existing, onboarded tech that can cover a broader range of features and solve a broader range of problems?

Then, ask yourself

Are there more integrated solutions you can select that will allow you to maintain more business-critical features while consolidating other tech?

Which tech makes sense to deprecate based on consolidating to the high-level marketing problems, expected (or realized) ROI, and impact on the team?

5. What’s the impact of making a change?

Determine the implications of deprecating or consolidating the losing tech.

Interview users of that tech so you have a complete understanding of the impact that any change could have. 

Think about the “cost to deprecate” and either re-onboard existing tech to solve more of your business needs or onboard new tech that allows you to deprecate.

Measuring the impact 

There are a lot of ways to measure a tech stack, whether it’s speed to market, operational efficiencies, team satisfaction, contribution to growth, or the end result: the customer experience that it delivers. Once you’ve made strides in changing your stack, how can you tell that it’s driving a measurable impact on the numbers that matter?

Here are some suggested measurement metrics against common marketing problems that can help you track success. 

• Customer lifetime value/revenue per active customer
• Number of active customers/customer retention
• Customer satisfaction scores
• Average order value 
• Conversion rate
• Repeat purchase rate 
• Engagement rates
  

Does the tech stack that powers your customer experiences have overlaps, gaps, complexity, and cost inefficiencies? 

Now is the time to consolidate your customer data and marketing platform. An integrated solution like Ometria powers not only the data unification, insight, and activation agile marketing teams need to drive relevant and personalized campaigns, but it also has the robust feature set required to do the triggered campaigns, complex customer journeys, and autonomous optimization that drive maximum revenue. Find out more about our customer data and marketing platform for retailers.