Convert visits to sales to repeat purchases

The moment you start seeing more than a thousand unique visitors in just one day, we won’t be surprised if you’d be grinning ear to ear the entire week. But when weeks turn into months, you’ll then remember why you started off on this venture in the first place … and it wasn’t about just owning an immensely popular website.

People, like you, who’ve chosen to invest in eCommerce were most likely thinking along the lines of great ROI, revenues, and profits. Now that you have thousands of visitors, how would you like to have, say for a start, 1% of them buying the products on your site?

You know more about your own product prices; you do the math. But what might really interest you is that a slight change in that 1% conversion rate can already spell a big difference in your profits. Now imagine bringing that 1% up to at least 10%. That’s possible, but not if you simply rely on guesswork.

We rely on tests applicable to complex multi-variable systems, just like today’s typical eCommerce websites, in determining which combination of copy text, landing page images, form layouts, and background colours generate higher conversion rates.

Here’s how we’ll convert your visitors into buyers:

  • We’ll conduct A/B or even multivariate tests on your eCommerce website, thus eliminating guesswork in determining how to increase those conversion rates.
  • We’ll perform on-site and off-site web analytics to gain a deeper understanding of web usage to aid in our optimisation operations.
  • Through our expertise in copywriting, graphics and web designing, UI designing, and website QA, we can enhance and fine tune your site to give each visitor a uniquely engaging browsing experience.
  • We can also integrate CRM (Customer Relationship Management) systems so that you’ll have the technical advantage to turn one-time buyers into repeat customers.

Check our similar posts

Uncover hidden opportunities with energy data analytics

What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

The application of Data and IT could drive significant cost savings in company-owned buildings and vehicle fleets. Virtual energy audits can be performed by combining energy meter data with other basic data about a building e.g. location, to analyse and identify potential energy savings opportunities. Investment in energy dashboards can further enable companies to have an ongoing look at where energy is being consumed in their buildings, and thus predict ways to reduce usage, not to mention that energy data analytics unlock savings opportunities and help companies to understand their everyday practices and operating requirements in a much more comprehensive manner.

Using energy data analytics can enable an organisation to: determine discrepancies between baseline and actual energy data; benchmark and compare previous performance with actual energy usage. Energy data analytics also help businesses and organisations determine whether or not their Building Management System (BMS) is operating efficiently and hitting the targeted energy usage goals. They can then use this data to investigate areas for improvement or energy efficient upgrades. When energy data analytics are closely monitored, companies tend to operate more efficiently and with better control over relevant BMS data.

Benefits Realisation Frameworks – A Useful Handle

One of the greatest challenges of project management is maintaining top-down support in the face of fluctuating priorities. If you elect to take on the role yourself and are peppered by other priorities, it can be a challenge to exactly remember why you are changing things and what your goals are. Sometimes you may not even notice you have reached your goal.

The Benefits Realisation Chart-room

The Benefits Realisation Model is a framework on which to hang key elements of any project. These traditionally include the following, although yours may not necessarily be the same:

  • Definition of the project goal
  • Quantification of intended benefits
  • Project plan versus actual progress
  • How you know you reached your goal
  • Quantification of actual benefits

Another way of describing Benefits Realisation Frameworks is they answer four fundamental questions that every project manager should know by heart:

  • What am I going to do?
  • How am I going to do it?
  • When will I know it’s done?
  • What exactly did I achieve?

The Benefits Realisation Promise

An astounding number of projects fail to reach completion, or miss their targets. It’s not for nothing that the expression ?after the project failed the non-participants were awarded medals? is often used in project rooms. We’re not saying that it is a panacea for success. However it can alert you to warnings that your project is beginning to falter in terms of delivering the over-arching benefits that justify the effort.

When Projects Wander Off-Target

Pinning blame on participants is pointless when project goals are flawed. For example, the goals may be entirely savings-focused and not follow through on what to do with the windfall. At other times realisation targets may be in place, but nobody appointed to recycle the benefits back into the organisation. This is why a Benefits Realisation Framework needs to look beyond the project manager?s role.

Realisation Management in Practice

If the project framework does not look beyond the project manager?s role, then it is over when it reaches its own targets ? and can even run the risk of being an event that feeds entirely off itself. In order to avoid a project being a means to its own end, this first phase must culminate with handover to a benefits realisation custodian.

An example of this might be a project to centralise facilities that is justified in terms of labour savings. The project manager?s job is to build the structure. Someone else needs to rationalise the organisation.

In conclusion, the Benefits Realisation Framework is a useful way of ensuring a project does not only achieve its internal goals, but also remains a focus of management attention because of its extended, tangible benefits.

Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

Contact Us

  • (+353)(0)1-443-3807 – IRL
  • (+44)(0)20-7193-9751 – UK

Ready to work with Denizon?

Contact Us Today