Hush makes a noise about its data integration push to support a single source of truth

Mark Samuels Profile picture for user Mark Samuels June 8, 2023
The fashion retailer is using application and data integration tech to provide quick and easy access to crucial business information.


Retailer Hush grew quickly during the coronavirus pandemic and the retailer’s IT systems struggled to cope with new demand.

Like so many others, the firm, which sells its products online in the UK and Europe and in John Lewis department stores, needed to integrate disparate data sources in order to tap into accurate insight on sales trends and finance figures to people across the business. 

A decision was made to build more in-house technology capability in order to boost data access and increase business agility. According to  Brad Woodward, Head of Data at the women's lifestyle firm:

We wanted to make sure we kept the technology simple. And when we started to think about integration, which is obviously a key point for any business these days, we focused on how systems talk to each other and how you get data out of systems.

Hush submitted an RFP in June 2021. The initial shortlist included five vendors. After hands-on trials and demonstrations, they whittled that shortlist down to two – and SnapLogic came out as the winner in September of that year. Woodward recalls: 

SnapLogic trod the line nicely between being easy to do the quick things, but also having a lot of customizations and the ability to do more complex work. Some of the other platforms we evaluated seemed more like a blackbox in that regard and didn't give us the flexibility we were looking for.

Eighteen months on and SnapLogic sits at the heart of an integrated data stack. Hush uses the technology to move data between core enterprise systems, including order management, Microsoft Dynamics 365 ERP, Emarsys CRM, Google Analytics, Centric PLM, and Salesforce Commerce Cloud, says Woodward:

We use SnapLogic to hook those sources into our data warehouse, which is Google BigQuery. We then use the data to build reporting models, where we use dbt. And we have a reporting front end based on Domo, which gives users access to our curated data models that we build in dbt from all the data we've integrated via SnapLogic...It's opened up access to all of the data for people in our organization. And it's allowed us to connect up to the various data-generating systems in our business with greater ease and flexibility.

Changing business processes

Hush uses its joined-up data approach to spot spikes in product demand. Before introducing SnapLogic, the only way to find out how many products had been sold on the website was to log in to the ERP system and run a report, which would take up to 15 minutes to produce results. Now, SnapLogic pulls data from Salesforce and produces sales results in a dashboard. Woodward explains:

People can get an accurate answer within three minutes. That's incredibly important and useful. Like yesterday, we went live with a promotion and we could immediately begin to measure the impact of that activity. SnapLogic has enabled us to do things like that, which weren't possible before.

Woodward’s team are running a variety of integrations and pipelines. For example, the engineering team recently introduced the ability to click and collect items through the website – and SnapLogic made it easy to surface the right data in the right format:

We need to keep the list of available click-and-collect locations up to date from the supplier. And it was used on a daily basis to pass the latest list of updated link locations to our website, which ensure data is constantly connected and reflects the options in real life that our customers see on the website.

Using SnapLogic to integrate data sources means users have quick access to accurate data on sales, finance and supply chain. Re-use is another boon. Woodward points out that both the data and engineering teams benefit from the integration work that others complete:

We can combine all of those pieces of data that exist across the business in one place...We can really inform what is going on in our business and think about the actions the consumer is taking that we need to understand and get ahead of.

Making further plans

The retailer now wants to use its single source of data to support personalization strategies that ensure Hush offers relevant and interesting products to customers. With a strong, centralized data foundation in place, the aim is to start exploring data science, explains Woodward: 

Here's our understanding of data, we've benchmarked it through reporting, we know that it's correct, and people are using it. Now we can throw data science at it and begin to extract value. Over the next 12 to 18 months, we want to look at tailored personalization and recommendation systems, things like forecasting and optimization of certain operational procedures.

Looking back over the past 18 months, Woodward reflects that, in many ways, technology has been the easy part of the transformation process. It’s much tougher to ensure non-technical people understand the power of the tools at their disposal. His team ensures the benefits are understood and communicated regularly:

We've done show-and-tell and lunch-and-learn activities where we show things off to the business. It can be challenging because if you show SnapLogic to someone working in fashion retail, you will scare them. So, it's been about sharing what we're working on and communicating it but doing it in a way that you don't lose people.

Woodward advises other business and digital leaders who are looking at SnapLogic to make sure they have the right capabilities in-house to build a single source of truth that’s verifiable and useful:

Although it’s a low code/no code platform, I do think you need a data engineer or an application engineer to be able to work with it. As with anything where you are creating a load of assets within a central tool, you need to think about boring things like naming conventions and governance structures because otherwise you can still end up creating a centralized mess.

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