Business-to-business sales firms that use a dropshipping platform to fill orders often rely more on guesswork than hard facts. Those who want to do better than this often find themselves leveraging data-driven insights to optimize dropshipping operations. B2B-focused data analysis software can help specialists identify dropshipping trends and figure out what changes have to be made to improve their workflows.
There’s a good possibility that most B2B sales firms that work with outside fulfillment services are already sitting on a mountain of commercial data. Since there’s an equally good chance that they’re not doing anything with it, it’s likely that most managers will want to take on some new algorithms that will help them make data-driven decisions. Perhaps the best place to start is by searching for any new markets that dropshippers and their vendors could easily take up residence in.
Finding new market sectors to expand into
One study predicted that the global dropshipping market would grow to nearly $1.7 trillion by 2031. While that number includes a large number of personal and household merchandise, there’s a good possibility that B2B sales will make up a healthy percentage of that growth. Business managers need to identify dropshipping trends before they take off and get saturated by their competition.
Predictive data analysis is the best way to tackle this problem. By processing input data based on previous results, a software application can plot a trend and locate possible areas of growth. Doing so doesn’t actually require any generative artificial intelligence subroutines nor does this sort of analysis need training data before working with real material.
Sort algorithms take raw numbers as input along with a set of arguments. They parse through the information line-by-line and locate areas where a piece of raw information matches one of the arguments they were fed initially. Computer scientists have implemented extremely simple versions of this kind of software that are almost identical to the file location apps included with most modern desktop environments.
Such a system would be almost comically slow, however, so must B2B data analysis experts will instead grow binary trees over time.
Building b-trees to help identify dropshipping trends
Self-balancing information storage structures are used to power a number of Unix-style file systems. One surprising study found that the world’s digital networks hold more than 64.2 zettabytes of information. A good chunk of that is stored on file systems structured around b-trees. That means they’re more than capable of dealing with loads of commercial data.
At their most basic, a b-tree structures data in a way that makes sorting operations nearly as quick as sequential reads. Each time someone inserts or removes some information, such as a list of fulfillment vendors, the tree will update itself to stay equalized. That means nobody has to wait for long updates later on, which is important for companies that could get orders at any hour of the day. Every b-tree generalizes the entire tree structure, so nodes can have a virtually unlimited number of children.
Databases used to identify dropshipping trends are going to have to manage huge blocks of data almost constantly. That makes this technology an excellent fit for the industry. Information scientists could rig up a system where incoming updates get pushed in via an extensible markup language document. Whenever shipments go out or get delivered, the entire tree would balance itself.
Anything that upsets the careful arrangement would raise red flags all across the structure. That means everyone with access would probably know if someone entered faulty data. Internal pages always remain constant and the tree itself grows upward as more users put an increasing amount of demand on it.
Sophisticated data processing techniques are only as good as their application, however. Business managers will want to take the insights they gain and use them to find places where they can improve.
Locating holes in a dropshipper’s supply chain
Data scientists usually start to notice trends the moment that they begin putting bits of information into some kind of order. Drop-shipping can be a slow and arduous process if there are any breaks in the chain. Managers who don’t realize that their B2B sales are getting held back by shipping delays will usually find out when they sit down to look at their first data analysis sheet.
Specialists who want to identify dropshipping trends will have no difficulty spotting spikes in delayed shipments once all of the relevant data is aggregated on a single page. Conventional visualizations are usually sufficient to help people spot the most basic trends. A few new developments are changing the conversation surrounding this technology, however.
Raster graphics represent two-dimensional drawings as a series of pixels known as continuous tones. This makes it hard to scale or stretch them. Most people have experienced the jagged lines that crop up whenever they try to stretch a JPEG, PNG or BMP file.
Exporting B2B data analytics in the form of a vector image almost eliminates this problem entirely. Vector graphics are traditionally used for certain types of geographical mapping systems as well as video games. By leveraging their power to identify dropshipping trends, managers can predict the likelihood of slowdowns. Zooming in to get a closer look at vector charts is easy and won’t obscure anything. Retailers with an immense number of data points will especially appreciate that fact.
That’s good news because today’s complicated supply chain problems can confound even the most carefully designed business plan. Once companies have these insights, there’s several strategies they can use to act on it.
Acting on insights to optimize dropshipping
Serious data analysts can often act on insights in just a few minutes. For instance, dropshippers can use an online tool to browse through other retail stores and find out what their competitors are doing. Once they do, they can use said tool to find the hottest dropship products currently for sale and add them to their own inventory.
Doing so lets them get ahead of the competition while simultaneously providing a wider range of goods to their customers. Some managers may even choose to aggregate customer feedback and mail messages into the same dashboard so that they can see if anyone made complaints they can act on. Small structural changes to their site or shopping cart app are often easy to pull off, yet these can go a long way toward building a better brand image.
If something is out of stock from one of their suppliers, then they’ll want to point their carts to a fresh source. Like all things in the dropshipping field, product stocking issues usually have identifiable trends to them. Most managers should have enough information to make adjustments after a few months of selling a product. They might notice that dropshipping orders fail at certain times of the day or week. Once they know about this, setting up their B2B sales channels to automatically switch suppliers is trivial.
That means they’ll have more time to devote to generating more income.
Getting better returns on each sale
Only around one in ten dropshippers are successful in their first year. It’s likely that many people in the industry struggle to cover their payments. Without solid data about their operations, these entrepreneurs will probably leave the market altogether.
Those who find themselves struggling may want to eliminate all low margin products. In their rush to find things to sell, most beginning dropshippers will go after every product line that has a large market share. These kinds of things might be popular, but they’re also likely sold by many other competing businesses. Packaging, shipping and production costs all work to decrease the amount of profit from each unit sold in a competitive market segment.
By taking a closer look at each month’s sales figures, it should be obvious which goods aren’t worth selling. As companies get larger, they can return to selling many of these products because they’ll be able to move larger quantities at a given time. Data analysis software can help sellers identify any trends that seem to suggest a particular product just isn’t worth carrying for the time being.
Another area where data-driven insights can make a huge impact is in lead generation.
Generating dropshipping leads with a low capital investment
Chances are that few independent dropshipping companies are going to want to put a great deal of money into lead generation. Targeted advertising campaigns are among the easiest way to draw in customers who wouldn’t otherwise know about a particular brand. Structured campaigns often focus on first-party promotional campaigns, which focus on supplier sites.
Although it might sound weird to advertise on a dropshipping vendor site, the data shows it actually makes sense. Entrepreneurs can look at their sales databases to see which products bring the most number of incoming leads. They might then consider taking out ads on a manufacturer’s site so that they can draw in outside customers who are actively looking for a supplier of something they want.
Proprietors of any business that starts to promote themselves in this way might eventually get more incoming messages than they know what to do with. They can contract with a service that offers knowledge process outsourcing to take incoming calls and manage all the vendor relationships they need to deal with. This should give them much more time to focus on lead generation and find new customers to work with.
Growing firms will also want to start looking at ways to hold onto the clients they have and reduce their churn rate.
Plotting out churn rate trends
Commercial analysts will often identify dropshipping trends that suggest clients might be gravitating to one company over another over time. Shopping cart abandonment rates are nearly 70% across all industries. Software experts say that this would drop drastically if site managers would redesign their carts. It’s not always easy to know what customers want, however.
Paying close attention to abandonment trends can provide quite a bit of insight when it comes to working on the underlying code. Some dropshippers might find that their customers are repeatedly abandoning their orders when they’re trying to buy specific items. That might point to a bug, a dread link or it might even mean that retailers are regularly selling out of a popular product.
Fixing these problems might be as simple as changing a few lines of code or locating a new supplier. Without proper trend recognition, however, they might never get addressed. Those who take the time to identify dropshipping trends that could be impacting their business might also try some of the following techniques:
- Improve search engine marketing based around incoming web traffic
- Replace any automatically generated copy on their sites
- Post customer reviews of products
- Get rid of any outdated product listings
- Let clients check their balance online
Improved communication can also help to cut down on the amount of incoming support requests a dropshipper receives. More than likely, the majority of contact form messages result from a lack of communication. A national survey found that nearly three out of four shoppers had a problem with something they bought in the last year. That can translate into an overwhelming number of support requests.
Each time someone identifies a negative trend and corrects it, they’re reducing the risk of this happening. Giving customers a dashboard to check their own information can also cut down on how much support individuals need.
Freeing time up for further business research
Saving all this time translates into more freedom to find new products and forge additional business relationships. Analysts that identify dropshipping trends early can take advantage of them before the rest of the market does. That gives them a chance to get the jump on the competition and provide goods to their customers they wouldn’t be able to get anywhere else.
Specialists who want to reach niche customers may have the most to benefit from new developments in data processing technology. Nevertheless, almost everyone in the industry will want to give these solutions a try.
