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Case study: Selections reaps rewards of smart investment
Archived article dated Friday December 5th 2008
Retailer benefits from results-based payment model and increases online sales by 8% year on year with help from Avail Intelligence
Introduction
Online retail continues to steal a march on the high street, with year-on-year growth in online shopping in September reaching 14 per cent according to the IMRG Capgemini E-tail October Index. While online shopping will not replace other mediums completely, it is a channel that retailers large and small must explore, as it is redefining the market and changing the way products are bought and sold.
Selections is one retailer that understands the importance of maximising sales opportunities with a minimal outlay of resources.
The organisation
Founded 18 years ago, Selections is a catalogue and online mail order company based in Dorset. The family-run business initially offered a range of classical and jazz music on CD. Keeping this niche focus, the retailer's product line was expanded to include both books and DVDs. In 2002 the retailer diversified by adding garden furniture.
With an annual turnover of over £3 million, online sales have grown to account for nearly a third of the retailer's total sales. Selections has seen double-digit growth via its website year-on-year in the last eight years. Garden furniture has grown significantly since its addition and now accounts for half of all the retailer's sales.
The challenge
As the retail industry is constantly evolving Selections knew it risked being left behind unless it made rapid changes. While a strong product line will go a long way to keeping the retailer in the market, it is not enough to continue growing the business.
With a very limited marketing budget available, any investment had to demonstrate an immediate and measurable return to secure buy-in from the management team. Already possessing a large volume of user-generated data gathered from almost two decades of customer purchases, Selections wanted to make better use of this resource. The retailer began investigating ways in which the data could be analysed and used to improve online sales in different ways.
“Keeping pace with other successful online retailers is always on your mind, but it is not a really a business driver when you're a small retailer like ours,” commented Mark Slocock, head of website development at Selections. “We look to introduce solutions that will have an impact on conversion and average order values. But ultimately we have to balance that with the budget we have available to make improvements.”
“Solutions-based behavioural intelligence algorithms first came to my attention in 2004,” said Slocock. “That's a rather grand term for automatic analysis of data that tracks customer behaviour when browsing and buying online to help identify trends and suggest ways to continuously attract customers and increase their spend via the website. We reviewed two companies, both of which were new to the UK market, and there was very little to differentiate the vendors' product offerings.”
The solution
Following a short consultation period, Selections opted to partner with ecommerce specialist, Avail Intelligence to implement the Navigation Predictor module of its eMarketing Suite.
It is designed to help the customer during the shopping process by presenting the most relevant products or offerings based on the customer's browsing behaviour, such as what they put in their virtual basket or based on their previous transaction history. Personalising the experience in this manner means that the retailer is able to present the right product, at the right time, to the right customer.
“The decision in the end proved a simple one, despite the two similar products,” commented Slocock. “Avail's payment structure is based on a revenue-sharing model, meaning we don't pay if there were no tangible results. The alternative required us to make an upfront investment in excess of £100,000.”
Slocock added: “We needed a partner that could support us while we integrated the software into our site. Avail was also extremely flexible and happy to work around our needs, which was essential.”
Taking the decision to host the source code provided by Avail had a number of implications. First, Selections had to identify, develop and install the correct Java Run Time engines. It was then necessary to write a configuration file to pull off the initial past order history to populate the sales predictor module. Once set up, a second script was designed that could update the data set on an hourly basis.
Slock continued: “We went live with the solution in early 2004 following a five-day implementation period. Impressed at both the speed and ease that we were able to integrate the software in to the ecommerce platform we have not since had any support issues - it has been totally self-sufficient.”
Not only were we impressed by the ease and speed at which we were able to get the Navigation Predictor up and running
Results
Selections saw an immediate impact on sales thanks to the new technology.
There was an increase in sales of between five and eleven per cent on a month-to-month basis, which could be directly attributed to the Navigation Predictor, which includes functionality to track the impact it has on sales. In 2007, the solution increased online sales by 8.36 per cent, while the figure for 2008 currently stands at 8.72 per cent.
“As a small retailer, we know better than most the impact that seemingly small changes can have on your bottom line. With no direct investment in marketing, we do all that we can to maximise sales opportunities,” said Slocock. “Avail's revenue-sharing model has meant that we have been able to improve the relevancy of the site without any expenditure on our part, which has had a positive impact to online spending.”
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